Thierry Gautier
email: thierry.gautier@inrialpes.fr

João V F Lima
email: jvlima@inf.ufsm.br

XKBlas: a High Performance Implementation of BLAS-3 Kernels on Multi-GPU Server

Keywords: Multi-GPU, BLAS, Task Parallelism

In the last ten years, GPUs have dominated the market considering the computing/power metric and numerous research works have provided Basic Linear Algebra Subprograms implementations accelerated on GPUs. Several software libraries have been developed for exploiting performance of systems with accelerators, but the real performance may be far from the platform peak performance. This paper presents XKBlas that aims to improve performance of BLAS-3 kernels on multi-GPU systems. At low level, we model computation as a set of tasks accessing data on different resources. At high level, the API design favors non-blocking calls as uniform concept to overlap latency, even by fine grain computation. Unit benchmark of BLAS-3 kernels showed that XKBlas outperformed most implementations including the overhead of dynamic task's creation and scheduling. XKBlas outperformed BLAS implementations such as cuBLAS-XT, PaRSEC, BLASX and Chameleon/StarPU.

I. INTRODUCTION

Dense linear algebra and operations on matrices are fundamental subprograms in scientific applications and deep learning. The design of BLAS library [START_REF]An updated set of basic linear algebra subprograms (blas)[END_REF] makes easy the development of high performance applications. BLAS makes possible the cooperation of a good numerical method for solving accurately a domain specific problem and a highly tuned library implementation for dense linear algebra operations. For instance LAPACK relies on BLAS for performance portability. Several commercial (Intel MKL, AMD ACML, IBM ESSL) and open source (OpenBlas, ATLAS) implementations propose highly tuned algorithms. Hence, BLAS ensures performance portability of linear algebra routines. And, despite if acceptable criticism about the approach were formulated [START_REF] Igual | The flame approach: From dense linear algebra algorithms to high-performance multi-accelerator implementations[END_REF], [START_REF] Van Zee | Blis: A framework for rapidly instantiating blas functionality[END_REF], it became a standard building block in HPC.

Since the 70's, when BLAS was defined, its architecture varies a lot. Memory hierarchies in the 80's were captured by the definitions of BLAS level 2 and level 3 with higher arithmetic intensity. With the apparition of GPU in HPC a decade ago, GPU has continuously demonstrated its performance/energy ratio which makes it unavoidable for extreme scale computing. Nowadays NVIDIA V100 SMX2 has peak performance of 7.8 TFlops/s in double precision floating point number (DP). In comparison the high end 8180 Xeon platinum Skylake peak DP performance ranges between 1.5 TFlops/s and 2 TFlops/s depending of the real frequency due to turbo boost mode. Moreover, memory bandwidth has higher rate on GPU than CPU which is required for low arithmetic intensity applications. Hence, offloading computation to single or multi-GPUs has been an active research field [START_REF] Igual | The flame approach: From dense linear algebra algorithms to high-performance multi-accelerator implementations[END_REF], [START_REF] Chan | Supermatrix: a multithreaded runtime scheduling system for algorithms-by-blocks[END_REF]- [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF].

To better exploit all performance capacity, programmers must deal with challenging problems concerning latency of communication between host and GPU(s), memory limitation of GPU and, finally, load balancing in heterogeneous architectures. Nevertheless, accelerating BLAS on multi-GPUs in legacy applications imposes a tradeoff between performance with heavy code refactoring and overhead of drop-in replacement libraries.

Let us illustrate the level of performance of various multi-GPU libraries providing API with same LAPACK matrix layout as BLAS (or CBLAS) library. Figure 1 reports the GFlops/s for GEMM matrix-matrix multiplication with the following libraries: up-to-date version 1 of the library Chameleon [START_REF]Chameleon library[END_REF] on top of StarPU [START_REF] Augonnet | StarPU: a unified platform for task scheduling on heterogeneous multicore architectures[END_REF], BLASX [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], multicore CBLAS from OpenBLAS-0.3.3 and cuBLAS-XT from CUDA-9.0. The GEMM, pure CPU, has performance of about 762 GFlops/s (43% of the CPU peak, 5% of the GPU peak) 2 . Chameleon with StarPU reaches at most 2.8 TFlops/s (about 20% of GPU peak) due to mandatory conversion from LAPACK matrix layout to internal tile matrix representation. The cuBLAS-XT with 9.8 TFlops/s (70% of the peak) is able to process arbitrary large matrix but with overhead due to communication and grain size penalties (see section V-B in [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF]). BLASX showed more than 13 TFlops/s (95% of the peak) and, to the knowledge to the author, was the fastest library with LAPACK matrix layout representation. It is possible to call BLASX routines directly in legacy applications for the small set of routines implemented. XKBlas, presented in this paper, attained similar performance (95% of the GPU peak) compared to BLASX but outperforms it on smaller matrix dimensions.

Obtaining performance on GEMM from a legacy application with LAPACK matrix layout is easy on large matrices because GPUs have good occupancy. But (1) it assumes the fact that memory used for matrices should have been already pinned, and accounting the pinning time in performance degrades it.

(2) Real applications schedule several BLAS kernels with dependencies. Except XKBlas, proposed in this paper, all libraries of Fig. 1 with LAPACK matrix layout have synchronous semantics with strong guarantees about the CPU memory coherency after the operations. This point is a strong limiting factor: data on GPU after the end of BLAS routine may be transferred forth and back if new BLAS is scheduled. The lack of support to take into account composition of (BLAS) kernels is a performance penalty.

This paper presents XKBlas, a high-performance BLAS library to exploit multiple GPUs, based on the XKaapi runtime system [START_REF] Hermann | Multigpu and multi-cpu parallelization for interactive physics simulations[END_REF], [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF], [START_REF] Lima | Design and analysis of scheduling strategies for multi-cpu and multi-gpu architectures[END_REF]. The main contributions of XKBlas on multi-GPU BLAS for HPC legacy applications are two simple and powerful features:

1) Composition of kernels. XKBlas allows to describe a sequence of any BLAS kernels to be scheduled on resources. Each BLAS kernel is decomposed into tasks with data flow dependencies and the runtime manages dependencies between tasks of different kernels. At runtime, the data flow graph between computational tasks is unfold and scheduled thanks to the XKaapi runtime system. 2) Explicit coherency operation. XKBlas lets the user to express data transfers explicitly between resources. Memory of GPUs are viewed as cache, and data transfers are a meaning of forcing update to the main host memory. We base our solution on re-using fine grain tasks from XKaapi that allows to integrate complex operations with dependencies among other operations as a XKaapi task. Task management and data flow dependencies have low overhead [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF]. It is one of the reasons that XKBlas outperformed BLASX and cuBLAS-XT in Fig. 1, which do not implement such dependent task model.

We evaluated XKBlas on two multi-GPU systems over cuBLAS-XT, PaRSEC and Chameleon/StarPU. XKBlas consistently outperformed them on all systems (4 NVIDIA P100 SMX2, 2 NVIDIA V100 PCIe, and 4 NVIDIA V100 SMX2). In comparison with NVIDIA cuBLAS-XT, XKBlas demon-strated better scalability with up to on average 188% performance gain and 450% less communication volume during all experiments.

The remainder of the paper is organized as follows. Section II analyzes the background and related works. Section III reviews the proposed XKBlas library and the XKaapi runtime system. We detail design and implementations of XKBlas and the interaction between XKBlas and XKaapi in Section IV. The experimental results of XKBlas against existing state-ofart implementations are presented in Section V. Finally, we conclude the paper in Section VI.

II. BACKGROUND AND RELATED WORKS

A. Multi-GPU BLAS libraries

There are several libraries that provide dense linear algebra algorithms for BLAS an LAPACK routines. Several works [START_REF] Igual | The flame approach: From dense linear algebra algorithms to high-performance multi-accelerator implementations[END_REF], [START_REF] Tomov | Towards dense linear algebra for hybrid GPU accelerated manycore systems[END_REF], [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF], [START_REF] Buttari | A class of parallel tiled linear algebra algorithms for multicore architectures[END_REF] assume matrix representation with tile data layout. Tile algorithms create tasks that operate on contiguous memory tile in order to reduce cache penalty and to increase performance. But this representation comes at the price of rigidity in further decomposition of tiles that could not be made without copy or other matrix representation as in PaRSEC [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF]. Furthermore, when porting tile algorithms on multi-GPU, the communications of sub matrices to GPU make them contiguous on GPU. In this context, tile representation on the host is irrelevant.

Several libraries [START_REF] Tomov | Towards dense linear algebra for hybrid GPU accelerated manycore systems[END_REF], [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF], [START_REF] Charara | Kblas: An optimized library for dense matrix-vector and matrix-matrix operations on gpu accelerators[END_REF], [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], [START_REF]cublasxt[END_REF] offer LAPACK subroutines on the (legacy) LAPACK matrix representation. Few of them are designed to be drop-in replacement (cuBLAS-XT [START_REF]cublasxt[END_REF] thanks to the NVBLAS wrapper and BLASX [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF] but public source code only contains general matrix-matrix multiplication BLAS).

B. Overlapping of communication by computation

The overlap of communication and computation is a common strategy in order to reduce the impact of communication latency between CPU and GPU on slow PCIe bus. One strategy is to exploit multiple CUDA streams with asynchronous communications with pinned memory as in StarPU [START_REF] Augonnet | StarPU: a unified platform for task scheduling on heterogeneous multicore architectures[END_REF] and XKaapi [START_REF] Hermann | Multigpu and multi-cpu parallelization for interactive physics simulations[END_REF], [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF], then more recently BLASX [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF] and PaR-SEC [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF]. StarPU, BLASX and cuBLAS-XT enqueue input operands and kernel into a same stream and overlapping comes from the use of several streams.

Another strategy from XKaapi [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF] runs each operation type over a separate stream (host-to-device copy, device-to-host copy or kernel execution) with multiple streams for kernel operation in order to let the GPU scheduler execute them concurrently if possible. PaRSEC [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF] has adopted the same strategy.

C. Multi-GPU software cache

A distributed caching mechanism is well-known approach in order to hold copies of host data into disjoint address spaces such as GPUs. Several variations of modified MOSI protocol have been proposed [START_REF] Augonnet | StarPU: a unified platform for task scheduling on heterogeneous multicore architectures[END_REF], [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF], [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF] with impact on performance not really comparable due to the number of experimental variables involved (problem size, hardware, GPU memory size, GPU type and count). The notable protocols are BLASX that proposes a two-level cache mechanism to improve locality of data access to favor GPU-to-GPU communication, and XKaapi where the eviction strategy prioritize eviction of read only data first. We modified XKaapi to better select the source device involved into a data transfer in order to favor the closest GPU-to-GPU transfer if possible, and potentially through a high speed NVLINK interconnect.

III. XKBLAS OVERVIEW

Figure 2 overviews XKBlas steps from a dependency graph to execution on a multi-GPU system. XKBlas [START_REF]Omitted for blind review[END_REF] links together two distinct parts: a set of tiled BLAS-3 linear algebra algorithms [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF], [START_REF] Buttari | A class of parallel tiled linear algebra algorithms for multicore architectures[END_REF], and the XKaapi runtime system for scheduling tasks with data dependencies over multi-GPUs [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF]. The tiled version of dense linear algebra code [START_REF] Buttari | A class of parallel tiled linear algebra algorithms for multicore architectures[END_REF] unrolls a data flow graph with a degree of parallelism that depends on matrix distributions (upper part of Fig. 2).

Then the scheduling algorithm uses the owner-computes rule heuristic to map a task on resources (Fig. 2(a)): a task is mapped to the resource owning its input matrix block. If no owner exists then the runtime makes a random choice among resources. Then the XKaapi runtime system distributes (Fig. 2(b)) the task and data among resources. It controls the distributed execution of tasks, schedules communication and tries to overlap latency with kernel execution.

A. Matrix representation and distribution

The BLAS-3 tiled algorithms of XKBlas are based on PLASMA [START_REF] Buttari | A class of parallel tiled linear algebra algorithms for multicore architectures[END_REF] and Chameleon [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF], which rely on tasks and data dependencies to unfold parallelism. Although both use tile matrix representation, XKBlas has the standard LAPACK matrix data layout (with colmajor storage) which allows to perform dynamic and recursive sub-partitions.

In the column major data layout from LAPACK, the memory region of a matrix starting at address A is entirely described by the tuple (m, n, ld, wordsize), m, n are matrix dimensions, ld is the leading dimension and wordsize the size in byte of an element of matrix. The tuple (m, n, ld, wordsize) is called the memory view of the matrix. This representation does not change with decomposition operation: sub matrices have the same representation.

A matrix A in XKBlas is a pair of (address,memory view) which can be copied or transferred between GPUs.

Once copied, the memory view of (sub)matrix A is (m, n, m, wordsize), i.e. the leading dimension always becomes the row dimension. We said the matrix has been compacted to a tile form.

The runtime maintains the preferred master resource of each matrix or submatrix in order to improve data mapping. For any matrix block A ij that appears during computation, preferred_map(A ij ) returns the location of the resource that stores a valid copy of A i j. Initially the returned value is ANY meaning that any resource is the preferred master resource. Once a task updating A ij is completed on resource R k , the runtime updates the preferred_map for A ij to R k .

The user may decide to set explicitly the preferred master resources for each block of a matrix or by calling xkblas_map_1Dblock_cyclic or xkblas_map_2Dblock_cyclic functions that only set the mapping information for all matrix blocks in 1D or 2D distribution over resources. XKBlas also proposes functions xkblas_distribute_2Dblock_cyclic_async or xkblas_distribute_1Dblock_cyclic_async to update the mapping information and migrate the blocks to the corresponding resources until the memory resources are full.

The mapping information is used by the scheduler to implement the owner-computes rule heuristic. Block cyclic and owner-computes rule are basic scheduling algorithms for mapping task to GPUs. cuBLAS-XT also relies on them.

B. Tiled algorithms

XKBlas currently implements the following algorithms: GEMM, SYMM, TRSM, TRMM, SYRK, SYR2K, HEMM, HERK and HER2K for classical precision: S (single precision floating point number), D (double precision), C (complex, single precision) and Z (complex, double precision).

XKBlas algorithms comes with the tile version of corresponding algorithms in Chameleon [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF] with the following modification:

• Tile representation are replaced by sub matrix representation using LAPACK data layout; • Instructions to copy back a matrix block to the host have been suppressed because they introduce extra data transfer between device and host; • LAPACK matrix data layout is required by legacy applications so the tile representation API has been discarded; • Extended LAPACK API with asynchronous semantics is the only internal XKBlas API for BLAS.

We extend matrix-matrix multiplication by providing a XGEMMT BLAS level 3 routine, similar to Intel MKL, that computes the general matrix product A × B but only updates the upper or lower triangular part of the result matrix. This is useful when the result is known to be symmetric, such as some computations in MUMPS [START_REF] Amestoy | A fully asynchronous multifrontal solver using distributed dynamic scheduling[END_REF] or WSMP [START_REF] Gupta | Effective minimally-invasive gpu acceleration of distributed sparse matrix factorization[END_REF]. The algorithm only creates tasks to update the triangular part. On the diagonal, due to the lack of similar routines, we call cuBLAS XGEMM.

C. Composition of BLAS routines

Integration of GPU in the sparse linear solver WSMP [START_REF] Gupta | Effective minimally-invasive gpu acceleration of distributed sparse matrix factorization[END_REF] goes beyond BLAS acceleration. Authors have proposed in ACCEL WSMP API to capture some compositions of BLAS calls during their sparse Cholesky factorisation in order to provide optimized version, e.g. with DTRSMSYRK which composes one DTRSM followed by one DSYRK. In [START_REF] Sao | A distributed cpu-gpu sparse direct solver[END_REF] this is the Schur complement update that is subject to optimization by on composition, aggregation to increase arithmetic intensity of GEMM and pipeline.

In XKBlas any sequence of BLAS calls could be composed in order to let the runtime better schedule tasks and manage communication. Moreover, XKBlas proposes a set of API methods to force cache invalidation which is coherent with the rest of the API. We also developed a multi-GPUs GEMMT that updates triangular part of matrix-matrix product which is extensively used in numerical solver such as MUMPS [START_REF] Amestoy | A fully asynchronous multifrontal solver using distributed dynamic scheduling[END_REF] when input problem is symmetric.

IV. XKBLAS INTERNALS

This section describes the implementation details of XKBlas such as its runtime system XKaapi, API calls for cache asynchronous execution, and composition of BLAS kernels.

A. Inherited task model and scheduling

XKaapi is a macro data flow runtime that creates, at runtime, tasks and themselves may spawn child tasks [START_REF] Hermann | Multigpu and multi-cpu parallelization for interactive physics simulations[END_REF], [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF]. Each task must describe the access mode to the memory for each of its formal parameter (read, write, etc).

XKaapi implements a non-preemptive (work stealing) scheduler, i.e. once started a task runs to completion. In order to avoid data hazards, there are constraints on the modes of access between the formal parameters and the effective parameters [START_REF] Galilée | Athapascan-1: On-line building data flow graph in a parallel language[END_REF]. The "sequential" semantics comes from Athapascan-1 [START_REF] Galilée | Athapascan-1: On-line building data flow graph in a parallel language[END_REF]: a value read by a task is produced by the last previous task with write access following the sequential order of execution.

At runtime, XKaapi computes the true dependencies between tasks and builds a data flow graph that represents the future of the computation. The runtime is in charge of transfers of input data (read, read-write access mode) and makes data allocation before starting tasks. XKaapi manages memory resources as a distributed shared memory.

In XKaapi each GPU has its own queue of ready tasks. A thread, bound to a CPU core closed to the GPU it manages, tries to execute at most w-tasks, where w is the window size (generally two in XKaapi) of concurrency on GPUs or it pulls for completion of asynchronous communication. The task execution relies on K-Stream [START_REF] Gautier | Xkaapi: A runtime system for data-flow task programming on heterogeneous architectures[END_REF] to handle communication and kernel execution.

When a task finishes, it may activate successor tasks that are pushed to the queue of a GPU that stored the output tile matrix. Among the available scheduling algorithms in XKaapi [START_REF] Lima | Design and analysis of scheduling strategies for multi-cpu and multi-gpu architectures[END_REF], we have only kept the owner compute rule strategy in XKBlas to map a task on the GPU that stores one of its output. If none of the task outputs is already mapped to GPUs, the library push the task to a random selected GPU.

B. Distributed Cache and Coherency operator

To execute a task, the scheduler creates a local copy of each parameter and transfers input data from a valid copy located on a GPU or main memory. The runtime keeps track of address spaces, data copies and their state. The decision about the source address space is always to select the closest with respect to the GPU topology or at random if several resources have a valid copy at the same distance.

After a synchronisation point, all tasks previously spawned, and their descendants, are completed. Nevertheless, host memory remains non-coherent with previous results of computation: new tasks could be spawned and the runtime will transfer data among resource, but the user could not directly read the host memory to access the result. He must explicitly ask the runtime to make coherent the host memory with respect to all the updated copies on the GPUs. XKblas has a function to update the upper or lower (or both) triangular part of a matrix on the host called xkblas_memory_coherent_async. Its implementation simply spawns a task for each block of matrix A i,j concerned with triangular part. The task takes a read access mode on the block and initiates the asynchronous copy back to the host. The operation is asynchronous and completion is guaranteed after the next synchronisation point. Note that a complementary function allows to request only one tile to be coherent.

C. Asynchronous API design

All XKBlas operators have a non blocking semantic: the caller should explicitly issue a synchronisation call to ensure that previous asynchronous operations have completed. XKBlas low-level routines define non-blocking function calls for computation, data annotation and memory coherency.

XKBlas high-level methods have CBLAS and Fortran BLAS entry point with blocking semantics. Typically the XGEMM function is implemented on top of non-blocking API using the following sketches: The xkblas_dgemm_async call returns immediately after pushing a request to make coherent full C matrix (upper and lower parts). Visibility of the request is ensured after the next synchronisation point xkblas_sync that waits until completion of all previous spawned tasks and their children.

D. CUDA memory register call

To be able to overlap transfers between device and host with kernel execution, transferred data must have been registered to CUDA using cudaHostRegister. The purpose is to page lock the memory in order to let DMA to transfer data. Nevertheless, the cost of this function is significant especially when it is difficult to reuse already pinned memory. Moreover, we have noticed that the total time spent in this cudaHostRegister call is multiplied by 2 when using 4 GPUs instead of 1 GPU.

The XKBlas API provides an asynchronous function called xkblas_register_memory_async to overlap the memory pinning by other operations (computation, matrix assembly, ...). The host registration is done by a specific thread using HostRegisterPortable flag and the result is visible to all CUDA contexts as ensured by the CUDA specification: "memory returned by this call will be considered as pinned memory by all CUDA contexts, not just the one that performed the allocation". This function introduces an implicit synchronisation with future computational kernels which are launched only when all requests to page-lock data accessed by task are completed.

E. Composition of BLAS kernels

In XKBlas all kernels are invoked through asynchronous function calls such as xkblas_dgemm_async. The feature is the simple proposal for composition of BLAS kernels in XKBlas. Composition is noted to be one of the key point for reaching high performance in sparse direct solver [START_REF] Gupta | Effective minimally-invasive gpu acceleration of distributed sparse matrix factorization[END_REF], [START_REF] Sao | A distributed cpu-gpu sparse direct solver[END_REF] such as MUMPS [START_REF] Amestoy | A fully asynchronous multifrontal solver using distributed dynamic scheduling[END_REF].

Moreover, if two tasks generated by the same thread and the first one writes while the second reads the same tile, they would create a true dependency thanks to the asynchronous semantics of the XKaapi runtime. Thus any sequence of user function calls generating tasks would allow to define point to point synchronisation between tasks among different function calls. The absence of synchronous semantics that force synchronization between calls permits to keep busy the GPUs. Other BLAS library runtime (Chameleon/StarPU, Magma, PaRSEC) expose asynchronous tile API for asynchronous function calls in order to favor composition but they impose implicit coherency on synchronisation point. cuBLAS-XT has synchronous invocation of BLAS kernel.

Instead of a set of implicit data transfers after kernel completion, XKBlas adopts a lazy approach where the user should describe which matrix or subparts of matrix has to be made coherent on the CPU. This is the key point for efficient composition of BLAS subroutines to avoid unnecessary data transfers.

The sequence of one BLAS kernel, that generates computational tasks, followed by a call to xkblas_memory_coherent_async is a typical composition that allows to overlap computation with data transfers back to the CPU. At runtime, because of the data dependency, the transfer to CPU memory is executed as soon as tile results are computed. In Chameleon/StarPU, to initiate as soon as possible such transfer of result to CPU, each tiled algorithm unrolls a data flow graph with annotation to flush back when the computed tile is done. The drawback of this approach is extra data transfers between host and GPUs a priori to the real composition of tiled algorithms. Nevertheless, in XKBlas the user has an explicit control over the usage of communication links between CPU and the GPUs which are a shared and limited resources.

V. EXPERIMENTAL RESULTS

Experiments have been made on two multi-GPU systems described in Table I. The interconnect is PCIe (Gen3) on Chifflot, and NVLINK-1 on Blaise. We used the public version of BLASX [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], version 1.2.6 of StarPU and Chameleon with up-to-date git hash g1f14c6b25. I) using double precision routines. Matrices are initialized with random numbers. We evaluated XKBlas performance against cuBLAS-XT and BLASX that have LAPACK matrix data layout. Note that even if the authors of BLASX reported performance with almost all BLAS L3 kernels in [START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], the public available code only contains GEMM routines.

A. Comparison with state of the art multi-GPU libraries

Each point was a mean of 8 runs. For each matrix dimension and runtime system, we only report the performance corresponding to the tile size that maximizes it among the experimented tile sizes (1024,2048,4096). Time to transfer data to GPUs and results to the host was included. We excluded the time to page lock the memory because applications should have the capacity to amortize its cost when using the same memory multiple times.

XKBlas outperformed other libraries for all configurations. Note that the performance of XKBlas using 1 GPU was better than cuBLAS-XT with 2 GPUs. Performance of XKBlas over 2 GPUs was similar or better than the performance of cuBLAS-XT with 4 GPUs.

B. Composition of BLAS TRSM+GEMM

We built a benchmark composing TRSM and GEMM BLAS kernels as it appears on the MUMPS application [START_REF] Amestoy | A fully asynchronous multifrontal solver using distributed dynamic scheduling[END_REF]. In [START_REF] Gupta | Effective minimally-invasive gpu acceleration of distributed sparse matrix factorization[END_REF] the authors report such fundamental Figure 4 reports performance and cumulative size in GByte of data transferred from host to GPUs (green, label H2D), GPUs to host (blue, label D2H) and GPU to GPU (red, label D2D) on three set of matrices and on four GPUs. First, cuBLAS-XT showed the highest communication volume. Moreover, it never uses the fast device to device NVIDIA NVLINK communication link (label D2D), which impacted its performance.

XKBlas had the lowest communication volume compared to others. As presented in Section IV-E, XKBlas allows to reduce the volume of communication between GPUs to host (blue D2H part in the bar chart) by decoupling completion of kernel to communication of results. The programmer is responsible for calling the necessary function to make the host memory coherent.

We note that on bigger dimensions (≥ 10k) XKBlas outperformed Chameleon on this composition because of the higher communication footprint of Chameleon, which was about 2 times greater than XKBlas. Chameleon performed better on smaller matrices.

C. Performance of Tile versus LAPACK layout

Figure 5 reports experiments with runtime systems that have LAPACK matrix layout representation. It has been argued that tile matrix representation, where each tile is contiguous in memory, is more friendly to cache and TLB [START_REF] Agullo | Faster, Cheaper, Better -a Hybridization Methodology to Develop Linear Algebra Software for GPUs[END_REF], [START_REF] Buttari | A class of parallel tiled linear algebra algorithms for multicore architectures[END_REF]. PaRSEC [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF] has hybrid matrix representation: at the coarse level, matrix is stored with tile matrix representation. Each coarse tile may be decomposed into fine tiles with LAPACK matrix layout.

In XKBlas, a GPU always holds a tile as contiguous memory region. Data transfer between GPU and host relies on cuMemcpy2DAsync that allows to change online from/to LAPACK matrix layout to/from contiguous memory region. A relevant question would be: What is the real gain of tile representation when most of the dense linear algebra computations are performed on GPUs on contiguous memory region? We partially give an answer with Figure 5 which reports experimental results of DGEMM with tile matrix representation of Chameleon [START_REF]Chameleon library[END_REF] and PaRSEC [START_REF] Wu | Hierarchical dag scheduling for hybrid distributed systems[END_REF]. In all configurations, the time encompass data transfer of the operands and transfer of the result matrix to the host. Memory was already pinned before timings. On Chifflot (V100 dashed lines) there was no notable difference of using LAPACK matrix layout of XKBlas versus the tile matrix representation of Chameleon. On Blaise (P100, solid lines) XKBlas outperformed Chameleon and its tile representation. We suspect that most of the performance gap was due to StarPU under Chameleon rather than the tile representation. At matrix size of 32768, Chameleon/StarPU has systematically reported a bad performance without a clear explanation. PaRSEC was the less performant runtime system and it seems to suffer from high overhead in management of large number of small tiles.

We argue that forcing tile matrix representation in complex runtime systems for dense linear algebra on multi-GPUs is counterproductive on addressing the problem of accelerating legacy application. Tile representation, which aims to promote strong code modifications, seems not competitive with libraries such as XKBlas or even BLASX.

VI. CONCLUSION

In this paper we presented XKBlas, a high-performance BLAS-3 library to exploit multi-GPUs based on the XKaapi runtime system. The main contributions of XKBlas are based on two powerful concepts: asynchronous function calls to compose BLAS kernels; and explicit operator to make coherent CPU that allows to move less data during a composition of BLAS. Scheduling is based on owner compute rule with auxiliary operators to give hints to the scheduler. Moreover, our experimental results showed that XKBlas outperformed BLASX and cuBLAS-XT in almost all configurations or it reaches equivalent performance results.

XKBlas has the potential to be widely used by the scientific community on legacy applications relying on dense linear algebra operations. This paper focus the API and performance of GEMM kernel but the library has complete set of BLAS level 3 kernel. XKBlas currently develops heuristics for a better use of huge memory capacity of multi-GPUs in order to increase the bandwidth and reduce latency in GPU-to-GPU communication.

Fig. 1 .

 1 Fig. 1. Performance DGEMM on 2 V100-PCIe NVidia with several libraries that provide BLAS routines on LAPACK matrix layout.

Fig. 2 .

 2 Fig. 2. Overview of XKBlas/XKaapi steps.

Figure 3

 3 Figure3reports average performance results of DGEMM, DSYMM, DSYRK, DSYR2K, DTRMM and DTRSM increasing the matrix dimension. We setup benchmarks over Blaise (TableI) using double precision routines. Matrices are initialized with random numbers. We evaluated XKBlas performance against cuBLAS-XT and BLASX that have LAPACK matrix data layout. Note that even if the authors of BLASX reported performance with almost all BLAS L3 kernels in[START_REF] Wang | Blasx: A high performance level-3 blas library for heterogeneous multi-gpu computing[END_REF], the public available code only contains GEMM routines.Each point was a mean of 8 runs. For each matrix dimension and runtime system, we only report the performance corresponding to the tile size that maximizes it among the experimented tile sizes(1024, 2048, 4096). Time to transfer data to GPUs and results to the host was included. We excluded the time to page lock the memory because applications should have the capacity to amortize its cost when using the same memory multiple times.XKBlas outperformed other libraries for all configurations. Note that the performance of XKBlas using 1 GPU was better than cuBLAS-XT with 2 GPUs. Performance of XKBlas over 2 GPUs was similar or better than the performance of cuBLAS-XT with 4 GPUs.

Fig. 3 .

 3 Fig.3. Performance of BLAS L3 kernels on 4 P100-SXM2 NVIDIA GPUs (Blaise) for several BLAS double precision routines with LAPACK matrix layout. Memory was already pinned before timings.

Fig. 4 .

 4 Fig. 4. Left: Cumulative size of data transfers on 4 GPUs during the composition of TRSM + GEMM between host and GPUs on Blaise and 3 size of matrices. Runs with cuBLAS-XT, Chameleon/StarPU (tile version) and XKBlas. Right: corresponding performance for varying matrix dimension on for GPUs.

Fig. 5 .

 5 Fig. 5. DGEMM comparison of XKBlas over Chameleon/StarPU and PaRSEC with tile matrix representation. Solid lines show performance on Blaise with 4 GPUs; dashed lines on Chifflot with 2 GPUs.

TABLE I MAIN

 I CHARACTERISTICS OF MULTI GPU SYSTEMS.

	Name	CPU	GPU
	Chifflot 2 Xeon(R) Gold 6126	2 NVIDIA Tesla V100-PCIE, 32GB
		2.6GHz	CUDA-9.0
	Blaise	2 Xeon E5-2699 v4	4 NVIDIA Tesla P100-SXM2, 16GB
		2.2GHz	CUDA-10.0

Git hash g1f14c6b25.

DP GEMM. Dual socket server (Chifflot V) is an Intel Gold 6126 has peak performance between 1.3 TFlops/s and 1.76 TFlops/s with attached 2 NVIDIA V100 PCIe 16GB GPUs at 7TFlops/s DP per GPU.

ACKNOWLEDGE

This work has been partially supported by the projects: UFSM/FATEC through project number 041250-9.07.0025 (100548); "GREEN-CLOUD: Computac ¸ão em Cloud com Computac ¸ão Sustentavel" (#16/2551-0000 488-9), from FAPERGS and CNPq Brazil, program PRONEX 12/2014.

Research leading to these results has in part been carried out on an UFRGS/Brazil server that was supported by Petrobras project 2016/00133-9.


Idir Benaissa

Katarzyna Gajda

Laure Vendier

Noël Lugan

Anna Kajetanowicz

Karol Grela

Véronique Michelet

Vincent César

Stéphanie Bastin

An anionic, chelating C(sp 3 ) / NHC ligand from the combination of N-heterobicyclic carbene and barbituric heterocycle

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

In transition metal chemistry, N-Heterocyclic Carbenes (NHCs) have established as one of the most prominent ligand types. 1,[START_REF] Díez-González | N-Heterocyclic Carbenes: From Laboratory Curiosities to Efficient Synthetic Tools[END_REF] Their accessibility, synthetic flexibility, 3,4 and the beneficial impact on the stability and catalytic, photophysical, or biological properties of their organometallic complexes are key features that have stimulated research in NHC organometallic chemistry. 5,6,[START_REF] Mora | Recent advances in gold-NHC complexes with biological properties[END_REF] Capitalizing on the strong and non-labile character of the metal-carbene bond, [START_REF] Chernyshev | The key role of R-NHC coupling (R = C, H, heteroatom) and M-NHC bond cleavage in the evolution of M/NHC complexes and formation of catalytically active species[END_REF] the NHC units have served in particular as pivotal, "anchoring" functions in polydentate ligand architectures. The introduction of an additional coordinating function, such as amine, N-heterocycle, alcohol, phosphine, or thioether on the N-side arm led to chelating or pincer-type heteroelement-NHC ligands. 9 Alternatively, connecting two or more NHC units led to the well-known poly-NHCs ligand class. [START_REF] Poyatos | Complexes with Poly(Nheterocyclic carbene) Ligands: Structural Features and Catalytic Applications[END_REF] Conversely, the development of anionic, LX-type C-NHC ligands has been relatively less explored, especially with a C(sp 3 ) carbon atom as second coordinating unit. A first subclass is constituted by bidentate hydrocarbyl / NHC ligands, in which a cyclometalation occurs on the NHC backbone at the benzylic, or a (primary or secondary) alkyl position as in A-C (Figure 1). [START_REF] Mo | Intramolecular C(sp3)-H Bond Activation Reactions of Low-Valent Cobalt Complexes with Coordination Unsaturation[END_REF][START_REF] Scott | Interaction of a Bulky N-Heterocyclic Carbene Ligand with Rh(I) and Ir(I). Double C-H Activation and Isolation of Bare 14-Electron Rh(III) and Ir(III) Complexes[END_REF][START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF][START_REF] Kruger | Rhodium-mediated activation of an alkane-type C-H bond[END_REF] Due to the high reactivity of the non-stabilized alkyl moiety, these cyclometalated complexes are usually highly sensitive to reagents/substrates. 15 A remarkable exception is shown by the Z-selective metathesis catalyst C, in which the chelating nature of the NHC ligand is a key feature to achieve the stereoselectivity observed during the reaction. The second sub-class consists of the combination of an NHC unit with a stabilized C(sp 3 ) ligand such as phosphonium ylide (D), 16  1 -fluorenyl (E), 17 or -cyanoalkyl (F) moieties (Figure 1). [START_REF] Oertel | Intramolecular Nitrile C-H Bond Activation in Nickel NHC Complexes: A Route to New Nickelacycles[END_REF] In the course of our ongoing research program on functionalized NHC ligands, 19 we have previously reported the synthesis of the stable anionic NHC 1  consisting of an imidazo [1,5a]pyridin-3-ylidene (IPy) 20 substituted by a pending anionic barbituric unit. We have shown that 1  is able to coordinate a gold(I) center through the carbene function only, the lateral anionic heterocycle remaining untouched and eventually available for further derivatization. [START_REF] Tang | An Original L-shape, Tunable N-Heterocyclic Carbene Platform for Efficient Gold(I) Catalysis[END_REF] Indeed, the anionic malonate moiety could be further O-functionalized by reaction with electrophiles, opening the way to diversity of ligand structures. As an extension of this work, we report herein a complete study on the coordination behavior of ligand 1  toward a series of d [START_REF] Chernyshev | The key role of R-NHC coupling (R = C, H, heteroatom) and M-NHC bond cleavage in the evolution of M/NHC complexes and formation of catalytically active species[END_REF] (Pd(II), Rh(I), Ir(I), Au(III)) and d 6 (Ru(II), Mn(I)) transition metal centers, demonstrating that 1  is also able to act as a stable, chelating and LX-type malonate-C(sp 3 ) / NHC ligand. Such a malonate-derived -alkyl ligand is quite rare in the literature, 22,[START_REF] Noguchi | Linkage Isomerism of Organoplatinum(II) Compounds Coordinated by two 1,3-Dimethylbarbiturate Anions[END_REF] and, to the best of our knowledge, has been incorporated only twice as constitutional unit in ancillary ligand. 24 Figure 1. Representative examples of anionic, bidentate C(sp 3 ) / NHC complexes. The coordinating C(sp 3 ) atom is highlighted with a grey sphere. Dipp: 2,6-diisopropylphenyl, Mes: mesityl.

RESULTS AND DISCUSSION

The zwitterionic precursor 1•H was easily deprotonated at room temperature in THF using a slight excess of lithium bis(trimethylsilyl)amide (LiHMDS) as a strong base, to give the stable free anionic carbene [1]Li in quantitative yield (Scheme 1). Its formulation was inferred in particular from its [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectrum, the resonance of the N2C carbenic carbon atom being observed at δC 199.2 ppm. [START_REF] Tang | An Original L-shape, Tunable N-Heterocyclic Carbene Platform for Efficient Gold(I) Catalysis[END_REF] This value is slightly shielded compared to the ones reported in the literature for classical free IPytype NHCs (206-209 ppm) [START_REF] Alcarazo | Imidazo[1,5-a]pyridine: A Versatile Architecture for Stable N-Heterocyclic Carbenes[END_REF] and might be indicative of a coordination of the carbene center to the lithium cation. 5b Treatment of [1]Li with 0.5 equivalent of [PdCl(allyl)]2 cleanly led to the formation of the corresponding air and moisture stable [Pd(allyl)(1)] complex 2 as a white solid in 75% yield after purification through a column chromatography (Scheme 1). Complex 2 was fully characterized by spectroscopic and analytical methods, which evidenced in particular the coordination of the carbenic and central malonate carbon centers on the Pd(II) center, reflecting a bidentate and chelating coordination mode. This could be deduced from the chemical shift of the NHC carbon atom recorded at C 170.7 ppm in the [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectrum, similar to related bidentate [Pd(allyl)(L^IPy)] complexes, 19a, 26 and by the shielding of the central malonic carbon atom from C 88.2 ppm in [1]Li to C 66.9 ppm suggesting a partial hybridization change from sp 2 in [1]Li to a more-pronounced sp 3 character. We had already observed the same behavior yet with a higher magnitude in a fully-organic 4,6-dioxopyrimidine compounds derived from the anionic maloNHC carbene (maloNHC = anionic 6-oxo-6H-pyrimidin-2-ylidene-4-olate). [START_REF] César | The Ambivalent Chemistry of a Free Anionic N-Heterocyclic Carbene Decorated with a Malonate Backbone: The Plus of a Negative Charge[END_REF] The molecular structure of complex 2 was then firmly established by a single-crystal X-Ray diffraction (Figure 2 and Table 1) and confirmed the chelating nature of ligand 1  , with a Pd1-C1 distance of 2.0191(19) Å, in the typical range of Pd-CNHC bond lengths, and a Pd1-C8 distance of 2.2241 (18) Å. The latter bond length appears significantly longer than other types of Pd-C(sp 3 ) bonds in chelating systems previously reported in the literature [2.10-2.17 Å]. 16, 22d, 24c, 28 This rather long Pd-C distance associated with the fairly acute bite angle C1-Pd1-C8 of 81.33 (7)° and the yaw angle   of 13.94° reflect the constrained ligand structure in 2. This significant yaw angle is quite similar to the yaw angles measured in complexes of the related iminophosphorane-IPy ligand, previously reported by us, and originates from the rigidity of the bicyclic imidazopyridine scaffold. 19a Finally, the noticeable pyramidalization of the malonate carbon (C8 = 344.86°) confirms the formulation of ligand 1  as an anionic bidentate C(sp 3 ) / NHC ligand. Scheme 1. Generation and coordination chemistry of anionic ligand 1  with d 8 metallic centers. COD: 1,5-cyclooctadiene, NBD: 2,5-norbornadiene.

The coordination abilities of ligand 1  were further investigated with other d 8 transition metals such as Ir(I) and Rh(I) metallic centers. Reaction of the free NHC 1•Li with [RhCl(nbd)]2, [RhCl(cod)]2 and [Ir(cod)Cl]2 as metallic precursors afforded the Rh(I) complexes 3 and 4, and the Ir(I) complex 6 in 60%, 82%, and 51% isolated yields, respectively. All three complexes were stable and could be purified by column chromatography. However, complex 6 appeared to be less stable in solution than its rhodium counterparts as slow de-coordination of the cod ligand was observed during the collection of NMR data. The 13 C NMR spectra of Rh(I) complexes 3 and 4 confirmed the chelating nature of ligand 1  as both malonic and carbenic carbons resonate as doublets at C 69.8 ppm ( 1 JC-Rh = 14.3 Hz) and 68.8 ppm ( 1 JC-Rh = 14.4 Hz) for the malonic carbon, and at C 166.8 ppm ( 1 JC-Rh = 60.8 Hz) ppm and 165.4 ( 1 JC-Rh = 55.2 Hz) ppm for the carbenic carbon in complexes 3 and 4, respectively (Table 2). The same analysis could be achieved on the Ir(I) complex 6 as the resonances of the carbenic and malonic carbon centers fall into the same range (C 165.8 and 70.6 ppm, respectively). [AuCl(1)](PPN) [b] 166.9 86.7 [a] In THF-d [START_REF] Chernyshev | The key role of R-NHC coupling (R = C, H, heteroatom) and M-NHC bond cleavage in the evolution of M/NHC complexes and formation of catalytically active species[END_REF] . [b] In CD2Cl2.

The molecular structures of complexes 3 and 6 were confirmed by single-crystal X-ray diffraction and both displayed a typical square planar geometry around the metal centers (Figure 2). While the ligand metrics (metal-CNHC and M-Cmalonate distances, bite and yaw angles) are similar to the ones previously recorded in complex 2 (see Table 1), it is worth to note that the Rh-CNBD and Ir-CCOD distances, which are trans to the carbene carbon center are longer than the Rh-CNBD and Ir-CCOD bond lengths trans to the malonate carbon atom, thus reflecting the more pronounced trans influence of the carbenic center. In order to evaluate the electronic properties of ligand 1  by IR spectroscopy, the dicarbonyl complex [Rh(1)(CO)2] complex 5 was synthesized from complex 4 by bubbling CO gas into a solution of complex 4 in dichloromethane. Complex 5 was isolated as an air and moisture stable yellow powder in 80% yield. It was fully characterized by analytical techniques supplemented by an Xray diffraction analysis (Figure 2). As expected, complex 5 displays a typical square planar geometry around the d 8 Rh(I) metal center. The CO values of complex 5 in CH2Cl2 solution were recorded at 2010 and 2069 cm -1 . Comparison of its average value (CO av = 2039 cm -1 ) with that of the structurally related rhodium complex [7](OTf) supported by an IPy-based ligand substituted with an iminophosphorane group in position 5 previously reported by our group (CO av = 2046 cm -1 ) revealed that replacing the neutral iminophosphorane moiety by the anionic  1 -barbituric moiety renders the corresponding ligand more donating (Figure 3). 19a Moreover, it appears that ligand 1  induces about the same overall electronic density on Rh(I) center as the strong electron-donating phosphonium ylide / NHC in [8](OTf). These results obtained with d 8 metallic centers encouraged us to explore the coordination chemistry of ligand 1  with gold(III). Our strategy rested on the oxidation of the gold(I) complex [AuCl(1)]Li, previously reported by us, using an external oxidant. Accordingly, [AuCl(1)]Li was generated in situ by reaction of free carbene 1•Li with [AuCl(tht)]. After evaporation of the solvent and without further purification, the resulting gold(I) complex was suspended in dichloromethane and reacted with iodobenzene dichloride PhICl2 (Scheme 2). The color of the suspension changed rapidly from dark green to yellow-orange. The 1 H NMR analysis of the crude reaction mixture after 20 min of reaction evidenced the formation of two different products in a 3/1 ratio, whose mixture was separated from impurities and by-products by column chromatography. Scheme 2. Oxidation of complex [AuCl(1)]Li with PhICl2.

The crystallization of the residue led to dark-green and orange crystals, which were separated manually. The X-ray diffraction analysis of the orange crystals confirmed the formation of the expected Au(III) complex 10 while the analysis of the green crystals evidenced the formation of the Au(I) complex 9, in which a C-Cl bond has been formed on the central malonic position of the barbituric heterocycle indicating a ligand oxidation (Figure 4, Table 3). Moreover, we noted that successive crystallizations of the mixture by slow evaporation of CH2Cl2 at room temperature led to the interconversion of the Au(I) complex 9, initially the major one, into the Au(III) complex 10, which could finally be isolated in a pure form in 72% overall yield.

In order to get a better understanding of this interconversion, the evolution of a concentrated solution (0.5 M) of complexes 9 and 10 obtained in an initial ratio 9/10 = 3/1 in dichloromethane was monitored by 1 H NMR. Aliquots were taken and analyzed in acetone-d6. The choice of the NMR solvent was driven by the good separation of the signals at 8.35 ppm and 8.20 ppm assigned to the remote proton on the imidazole ring in complexes 9 and 10, respectively. The monitoring evidenced a full conversion of complex 9 into complex 10 after 7.7 days. When performed in DCE (0.5 M) at 40°C, full conversion of complex 9 into complex 10 was obtained in 4.6 days. However, no reliable kinetic conversion could be measured despite numerous attempts. The transformation of 9 into 10 is supposed to occur through an intramolecular, SN2-type oxidative addition of the malonate-type C-Cl bond onto Au(I) center. 31 The gold(I) complex 9 displays the typical linear geometry coordination of gold(I) complexes with a C1-Au1-Cl1 angle of 177.64 (7)°. Due to the sp 3 hybridization character of the C8 carbon, the barbituric heterocycle is not entirely planar anymore, and the C8 carbon deviates by 0.449 Å from the mean plane formed by the C9-N3-C10-N4-C11 atoms with the chloride pointing in the opposite direction to the metal center. This specific geometry is consistent with an outer-sphere chlorination reaction and forces the two carbon atoms C9 and C11 to be closer to Au1 (Au1-C9 = 3.069 Å and Au1-C11 = 3.065 Å) than in complex [AuCl(1)]PPN (3.317 Å and 3.409 Å respectively). [START_REF] Tang | An Original L-shape, Tunable N-Heterocyclic Carbene Platform for Efficient Gold(I) Catalysis[END_REF] The Au(III) center in complex 10 displays the typical square planar geometry of gold(III) complexes with the ligand 1  chelating the metal center through coordination of the sp 3 malonic carbon C8 and the carbenic carbon C1.

Complexes 9 and 10 were fully characterized by 1 H and 13 C NMR. The 1 H NMR spectrum of 10 displays a doublet at 6.73 ( 3 JC-H = 6.8 Hz) ppm which corresponds to the proton in position 6 of the IPy bicycle. This signal is significantly shielded compared to its equivalent in the gold(I) complex [AuCl(1)]PPN (7.21 ppm), which can be explained by the coordination of the malonic carbon to the gold metallic center. This trend was already noticed in the previous complexes 2-6. Conversely, this proton appears to be deshielded at 7.72 ppm in complex 9 due to the presence of the chlorine atom on the malonic carbon. The 1 H and [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectra reflect the Cs-symmetry for both complexes 9 and 10, in which the IPy bicycle defines the symmetry plane in the molecule. In the [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectrum, the chemical shift of the malonic carbon atom is recorded at 67.5 ppm for gold(III) complex 10, which lies in the same range as the chemical shifts recorded for complexes 2-6.

The bidentate coordination mode of ligand 1  is not restricted to d 8 transition metals and was also observed in d 6 metal complexes. Indeed, the reaction between free NHC [1]Li with the [RuCl2(p-cymene)]2 and [MnBr(CO)5] metal precursors led to complexes 11 and 12 in 77% and 37% yields, respectively (Scheme 3).

Scheme 3. Synthesis of d 6 -metal complexes 11 and 12

Both complexes were fully characterized by spectroscopic and analytical techniques. In particular, the Cs-symmetry of the complex 12 is reflected by the presence of three signals in the [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectrum corresponding to the four carbonyl ligands: the two peaks at 215.3 ppm and 214.2 ppm are attributed to the carbonyl ligands lying in the plane of the IPy core while the signal at 210.7 ppm corresponds to the two carbonyl ligands on each side of the mirror plane materialized by the IPy bicycle. The molecular structures were firmly confirmed by X-Ray analysis (Figure 4). In both complexes 11 and 12, the ligand 1  displays a κ 2 -C,C bidentate coordination mode with quite acute bite angles of 77.43(17)° and 79.61(6)°, respectively and the highest degrees of sp 3 -pyramidalization within the series [C8 = 336.1° for 11 and 339.44° for 12]. The ruthenium complex 11 adopts an half sandwich distorted pseudo-octahedral geometry around the Ru(II) center with the η 6 -p-cymene occupying three facial coordinating sites and the anionic ligands 1  and Cl  completing the coordination sphere. While the Mn(I) complex 12 displays a distorted octahedral geometry, it is worth to note that the Mn1-C31 and Mn1-C33 bonds [1.8278(16) Å and 1.8230(17) Å, respectively], which are in the coordination plane of ligand 1  are significantly shorter than the Mn1-C30 and Mn1-C32 bonds [1.8632(18) Å and 1.8715(17) Å], perpendicular to this plane, due to a stronger backdonation from the Mn center into the *(CO) orbitals, and evidencing the strong donation of the ligand 1  .

Reports in the literature showed that ruthenium complexes supported by NHC ligands can promote the dehydrogenative synthesis of carboxylic acids from primary alcohols. 32 More specifically, a highly active catalytic system supported by a cyclometalated κ 2 -C,C bidentate NHC ligand was developed by Verpoort and coworkers running at catalyst loading as low as 25 ppm. [START_REF] Wang | Highly active bidentate N-heterocyclic carbene/ruthenium complexes performing dehydrogenative coupling of alcohols and hydroxides in open air[END_REF] Based on the typical reaction conditions established by Verpoort, we implemented complex 11 in the aerobic Rucatalyzed oxidation of benzylic alcohol into benzoic acid starting with 250 ppm of catalyst and 1.2 equiv of KOH in refluxing o-xylene (Table 4). 2. phere. b NMR yields were measured using 1,3,5-trimethoxybenzene as an internal standard. c Reaction performed under open argon atmosphere.

= [(N1-C1-M)-(N2-C1-M)]/2
The dehydrogenative coupling of benzyl alcohol and potassium hydroxide reaction was first performed under open argon conditions leading to the formation of benzoic acid 14a in 96% after 5 hours, confirming that molecular dioxygen is not involved in the oxidation process (entry 2). Operating under an open air atmosphere did not alter the activity of the catalyst, as the product 14a was obtained in 99% yield in only 3 hours (entry 8), highlighting the robustness and the convenient handling of the catalytic system. The subsequent experiments were consequently conducted under aerobic conditions. Oxidation of the benzylic alcohol was successfully performed at a low catalyst loading of 25 and 10 ppm to give 14a in 76% and 73% yields respectively (entries 10 and 12), leading to a maximum TON of 73000 (entry 12), yet at the expense of longer reaction times. A blank experiment was conducted in the absence of any ruthenium catalyst and traces only of benzoic acid were detected, showing the crucial role of the catalyst and ruling out a possible oxidation of benzylic alcohol under basic aerobic conditions (Entry 13). 34 For the sake of comparison, a second catalytic reaction was set up in the presence of [RuCl2(p-cymene)]2 dimer leading to very poor yield (9%, entry 14) demonstrating that the activity of the catalytic system relies on the nature of the ligand.

With the optimized conditions in hand (250 ppm of pre-catalyst 11 and 1.2 equiv of KOH in refluxing o-xylene for 6 hours), a series of primary alcohols was subjected to the dehydrogenative coupling reaction (Scheme 4). Benzylic alcohols displaying electron-donating groups in meta or para position 13b-e were successfully oxidized with good to excellent yields ranging from 83% to 97%, the substitution of the aromatic ring did not alter to a great extent the reaction yields. On the other hand, electron-poor substrates 13g-j were more reluctant to oxidation and lower yields (46 to 77%) were recorded despite an increase of the catalyst loading (500 ppm for substrates 13g-i) or longer reaction times (16 h for substrate 13j). It is worth noting that the oxidation of the halogenated substrates 13g and 13h afforded the corresponding acids 14g and 14h along with a non-negligible amount of dehalogenated benzoic acid 14a, this dehalogenation side-reaction being also observed by Verpoort and coworkers. [START_REF] Wang | Highly active bidentate N-heterocyclic carbene/ruthenium complexes performing dehydrogenative coupling of alcohols and hydroxides in open air[END_REF] The catalytic system was tolerant to the presence of an acidic function on the aromatic ring, as 4-hydroxybenzyl alcohol 13f was oxidized to the corresponding carboxylic acid in 49% yield in the presence of 3.3 equiv of KOH. The catalytic system is also compatible with polyaromatic alcohols (13k). Next, we investigated the dehydrogenative coupling of aliphatic alcohols 13l-p with potassium hydroxide. Aliphatic alcohols were successfully oxidized but were less reactive and longer reaction times (16 h) were required to obtain moderate to good yields (46-92%). It is worth noting that the presence of heterocycles did not inhibit the reaction. In particular, 3-pyridylpropionic acid 14m was isolated in 91% yield, proving the compatibility of the catalytic system with highly coordinating moieties. Introduction of a bulky adamantyl substituent resulted in a drastic decrease of the reaction yield, 14p being obtained in 31% yield only, to be compared to 92% yield for 14n. Eventually, the oxidation of hexanol led to hexanoic acid 14o in a moderate 68% yield. Overall, the efficiency of the present catalytic system based on complex 11 appears quite similar to the reference Verpoort's catalytic system.

CONCLUSION

Through a detailed coordination study, we have shown that the anionic ligand 1  , composed of an imidazo[1,5-a]pyridin-3ylidene laterally substituted by an anionic barbituric moiety, acts as a chelating, bidentate Csp3 / CNHC ligand on square-planar d [START_REF] Chernyshev | The key role of R-NHC coupling (R = C, H, heteroatom) and M-NHC bond cleavage in the evolution of M/NHC complexes and formation of catalytically active species[END_REF] metallic centers [Pd(II), Rh(I), Ir(I), Au(III)] as well as on (pseudo)octahedral d 6 metallic centers [Ru(II), Mn(I)]. Through the deformation of the barbituric heterocycle and pyramidalization of the central carbon atom of its malonic unit from sp 2 in free 1•Li to sp 3 , the ligand 1  afforded stable 5-membered metallacycles, displaying quite acute bite angles [77-82°] and noticeable tilting coordination of the carbenic center [yaw angles: 10-14°] due to the rigidity of its bicyclic scaffold. Most importantly, the ruthenium complex 11 proved to be highly efficient in the dehydrogenative oxidation of benzylic and primary alcohols, evidencing the potential of ligand 1  as a powerful supporting ligand in organometallic catalysis. This work constitutes the first report of such a coordination mode for an anionic barbituric heterocycle and we are currently working on further implementations of this novel ligand structure in other metal/NHC-catalyzed reactions.

Scheme 4. Scope of the Ru-catalyzed dehydrogenative oxidation of primary alcohols by using pre-catalyst 11. a a conditions: primary alcohol (3.75 mmol), potassium hydroxide (1.2 equiv), o-xylene (0.75 mL) and complex 11 (250 ppm) under air atmosphere; isolated yields. b 500 ppm catalyst used. c Yield of benzoic acid 14a.

EXPERIMENTAL SECTION

General information

All manipulations were performed under an inert atmosphere of dry nitrogen for the syntheses or of dry argon for the catalytic tests by using standard vacuum line and Schlenk tube techniques. Dry and oxygenfree organic solvents (THF, Et2O, CH2Cl2, toluene, pentane) were obtained using LabSolv (Innovative Technology) solvent purification system. [AuCl(tht)], [START_REF] Hashmi | New and Easily Accessible Nitrogen Acyclic Gold(I) Carbenes: Structure and Application in the Gold-Catalyzed Phenol Synthesis as well as the Hydration of Alkynes[END_REF] [PdCl(C3H5)2]2 36 and [RhCl(1,5-cod)]2, [START_REF] Giordiano | Di-μ-chloro-bis-(η4-1,5-cyclooctadiene)-dirhodium(I)[END_REF] and [RhCl(nbd)]2 [START_REF] Abel | Norbornadiene-Metal Complexes and some Related Compounds[END_REF] were synthesized according to literature procedures. All other reagent-grade chemicals were purchased from commercial sources and used as received. Chromatographic purification of the compounds was performed on silica gel (SiO2, 40-63 m or 60-200 m) or deactivated aluminium oxide (neutral Al2O3, Brockmann type III (4.7% water), 50-200 m). 1 H, 31 P, and [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectra were obtained on Bruker Avance 400, Avance III HD 400, or Avance 500 spectrometers and were referenced relative to the residual signals of the deuterated solvents ( 1 H and 13 C). [START_REF] Fulmer | NMR Chemical Shifts of Trace Impurities: Common Laboratory Solvents, Organics, and Gases in Deuterated Solvents Relevant to the Organometallic Chemist[END_REF] Chemical shifts were reported in ppm. 1 H and [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR signals were assigned by means of additional [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C{ 1 H, 31 P}, [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C-DEPT135, 1 H- [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C HMQC and/or HMBC experiments. Mass spectra (ESI mode) were obtained using a Xevo G2 QTof (Waters) spectrometer and were performed by the mass spectrometry service of the "Institut de chimie de Toulouse". Elemental analyses were carried out by the elemental analysis service of the LCC (Toulouse, France) using a Perkin Elmer 2400 series II analyzer.

[( 3 -allyl)[2-(2,6-diisopropylphenyl)-5-(1,3-diisopropyl-2,4,6trioxo-hexahydropyrimidin-5-yl-C 5 )imidazo[1,5-a]pyridin-3-ylidene-C 3 ]palladium(II)] (2)

n-BuLi (1.6 M in hexane, 268 µL, 0.43 mmol, 2.15 equiv) was added to a solution of HMDS (102 µL, 0.49 mmol, 2.45 equiv) in THF (3 mL) at room temperature. After 20 min, 1•H (200 mg, 0.41 mmol, 2.05 equiv) was added. The mixture was stirred at room temperature for 20 min and solid [PdCl(allyl)]2 (73 mg, 0.20 mmol, 1.0 equiv) was added at once. The solution was stirred overnight at room temperature and all volatiles were removed in vacuo. The residue was purified by flash chromatography (neutral Al2O3, Brockmann type III, CH2Cl2), washed with ether (5 mL) and dried to give a white solid (192 mg, 75%). Crystals suitable for an X-Ray diffraction experiment were grown by layering a solution of 2 in CH2Cl2 with pentane. 1 H NMR (400 MHz, CDCl37.48 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.30-7.19 (m, 3H, CH Py +CH m-Dipp), 7.15 (s, 1H, CH Im), 7.08 (dd, J = 9.2, 6.7 Hz, 1H, CH Py), 6.64 (dd, J = 6.6, 0.9 Hz, 1H, CH Py), 5.20 (hept, J = 6.9 Hz, 1H, NCH(CH3)2), 5.03 (hept, J = 6.9 Hz, 1H, NCH(CH3)2), 5.01-4.87 (m, 1H, CH Allyl), 3.53 (dd, J = 7.4, 2.2 Hz, 1H, CH2 Allyl), 2.85 (d, J = 13.4 Hz, 1H, CH2 Allyl), 2.43 (hept, J = 6.8 Hz, 1H, CH(CH3)2), 2.43 (d, J = 6.9 Hz, 1H, CH2 Allyl), 2.11 (hept, J = 6.8 Hz, 1H, CH(CH3)2), 2.09-2.04 (m, 1H, CH2 Allyl), 1.48 (d, J = 6.9 Hz, 3H, NCH(CH3)2), 1.45 (d, J = 6.9 Hz, 3H, NCH(CH3)2), 1.38 (d, J = 6.9 Hz, 3H, NCH(CH3)2)), 1.35 (d, J = 6.9 Hz, 3H, NCH(CH3)2)), 1.13 (d, J = 6.9 Hz, 3H, CCH(CH3)2)), 1.10 (d, J = 6.l8 Hz, 3H, CCH(CH3)2)), 1.06 (d, J = 6.9 Hz, 3H, CCH(CH3)2)), 1.01 (d, J = 6.8 Hz, 3H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] 60.52; H, 6.35; N, 8.82; found: C, 60.52; H, 6.29; N, 8.71.

[( 4 -norbornadiene)[2-(2,6-diisopropylphenyl)-5-(1,3-diisopropyl-2,4,6-trioxo-hexahydropyrimidin-5-yl-C 5 )imidazo[1,5-a]pyridin-3-ylidene-C 3 ]rhodium(I)] (3)

n-BuLi (1.6 M in hexane, 230 µL, 0.37 mmol, 1.2 equiv) was added to a solution of HMDS (90 µL, 0.37 mmol, 1.2 equiv) in THF (3 mL) at room temperature. After 20 min, 1•H (150 mg, 0.31 mmol, 1.0 equiv) was added, and the mixture was stirred at room temperature for 20 min. Then [RhCl(nbd)]2 (85 mg, 0.18 mmol, 0.6 equiv) was added all at once and the reaction mixture was stirred for 30 min. All volatiles were evaporated and the crude residue was washed with pentane (2×5 mL) to give an intense-orange solid (126 mg, 60%). Single crystals suitable for an X-Ray diffraction experiment were obtained by slow evaporation of a solution of 3 in pentane at room temperature. 1 H NMR (400 MHz, CDCl37.42 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.21 (d, J = 7.8 Hz, 2H, CH m-Dipp), 7.11 (dd, J = 9.2, 0.9 Hz, 1H, CH Py), 6.99 (dd, J = 9.2, 6.7 Hz, 1H, CH Py), 6.89 (s, 1H, CH Im), 6.54 (dd, J = 6.7, 0.9 Hz, 1H, CH Py), 5.16 (hept, J = 6.9 Hz, 2H, NCH(CH3)2), 4.06-4.04 (m, 2H, CH nbd), 3.58-3.55 (m, 2H, CH nbd), 3.49-3.47 (m, 2H, CH nbd), 2.40 (hept, J = 6.8Hz, 2H, CCH(CH3)2), 1.54 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.48 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.38 (d, J = 6.8 Hz, 6H, CCH(CH3)2)), 1. 18-1.16 (m, 2H, CH2 nbd) 1.06 (d, J = 6.8 Hz, 6H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] 61.57.; H, 6.21; N, 7.91; found: C, 61.41; H, 6.38; N, 7.73 (despite considerable drying under high vacuum, CH2Cl2 could not be removed in totality from the sample).

[( 4 -1,5-cyclooctadiene)[2-(2,6-diisopropylphenyl)-5-(1,3-diisopropyl-2,4,6-trioxo-hexahydropyrimidin-5-yl-C 5 )imidazo[1,5a]pyridin-3-ylidene-C 3 ]rhodium(I)] (4)

n-BuLi (1.6 M in hexane, 153 µL, 0.24 mmol, 1.2 equiv) was added to a solution of HMDS (60 µL, 0.29 mmol, 1.45 equiv) in THF (3 mL) at room temperature. The mixture was stirred for 20 min, and 1•H (100 mg, 0.20 mmol, 1.0 equiv) was added as a solid. The solution was stirred at room temperature for 20 min, then [RhCl(COD)]2 (50 mg, 0.10 mmol, 0.5 equiv) was added. After 1 hour, all volatiles were evaporated and the crude residue was purified by column chromatography (neutral Al2O3 Brockmann type III, CH2Cl2) and washed with pentane (5 mL) to give complex 4 as an orange powder (115 mg, 82 %). 1 H NMR (400 MHz, CDCl37.45 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.23 (d, J = 7.8 Hz, 2H, CH m-Dipp), 7.10 (d J = 9.1 Hz, 1H, CH Py), 6.96 (dd, J = 9.1, 6.7 Hz, 1H, CH Py), 6.87 (s, 1H, CH Im), 6.50 (d, J = 6.7 Hz, 1H, CH Py), 5.16 (hept, J = 6.9 Hz, 2H, NCH(CH3)2), 4.13-4.07 (m, 2H, CH COD), 3.81-3.75 (m, 2H, CH COD), 2.48 (hept, J = 6.8Hz, 2H, CCH(CH3)2), 2.20-2.12 (m, 2H, CH2 COD), 2.02-1.93 (m, 2H, CH2 COD), 1.79-1.72 (m, 2H, CH2 COD), 1.64-1.57 (m, 2H, CH2 COD), 1.49 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.47 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.31 (d, J = 6.8 Hz, 6H, CCH(CH3)2)), 1.09 (d, J = 6.7 Hz, 6H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] To a solution of 4 (57 mg, 0.08 mmol) in CH2Cl2 (2 mL) was bubbled gaseous carbon monoxide during 20 min, a color change from orange to yellow was observed. All volatiles were evaporated and the crude residue was washed with pentane (5 mL) to give complex 5 as a yellow powder (42 mg, 80 %). Single crystals suitable for an X-Ray diffraction experiment were obtained by crystallization from CH2Cl2/Et2O/hexane at room temperature. 1 H NMR (400 MHz, CDCl37.52 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.31-7.29 (m, 3H, CHm-Dipp + CHPy), 7.18-7.14 (m, 2H, CHPy + CHIm), 6.65 (d, J = 6.8 Hz, 1H, CH Py), 5.13 (hept, J = 7.1 Hz, 2H, NCH(CH3)2), 2.26 (hept, J = 7.0 Hz, 2H, CCH(CH3)2), 1.49 (d, J = 6.7 Hz, 6H, NCH(CH3)2), 1.48 (d, J = 6.6 Hz, 6H, NCH(CH3)2), 1.23 (d, J = 6.7 Hz, 6H, CCH(CH3)2)), 1.13 (d, J = 6.8 Hz, 6H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] , 57.59; H, 5.46; N, 8.67; found: C, 57.62; H, 5.45; N, 8.30.

[( 4 -1,5-cyclooctadiene)[2-(2,6-diisopropylphenyl)-5-(1,3-diisopropyl-2,4,6-trioxo-hexahydropyrimidin-5-yl-C 5 )imidazo[1,5a]pyridin-3-ylidene-C 3 ]iridium(I)] (6)

n-BuLi (1.6 M in hexane, 153 µL, 0.24 mmol, 1.2 equiv) was added to a solution of HMDS (60 µL, 0.29 mmol, 1.45 equiv) in THF (3 mL) at room temperature. After 20 min, 1•H (100 mg, 0.20 mmol, 1.0 equiv) was added. The mixture was stirred at room temperature for 20 min, and [IrCl(COD)]2 (68 mg, 0.10 mmol, 0.5 equiv) was added. All volatiles were evaporated and the crude residue was purified by column chromatography (neutral Al2O3 Brockmann type III, CH2Cl2) and washed with pentane (5 mL) to give complex 6 as a red powder (81 mg, 51 %). 1 H NMR (400 MHz, CD2Cl27.50 (t, J = 7.8 Hz, 1H, CH p- Dipp), 7.28 (d, J = 7.8 Hz, 2H, CH m-Dipp), 7.19 (dd, J = 9.1, 0.9 Hz, 1H, CH Py), 7.05 (dd, J = 9.1, 6.7 Hz, 1H, CH Py), 6.98 (s, 1H, CH Im), 6.50 (dd, J = 6.7, 0.9 Hz, 1H, CH Py), 5.08 (hept, J = 6.9 Hz, 2H, NCH(CH3)2), 3.81-3.79 (m, 2H, CH COD), 3.41-3.39 (m, 2H, CH COD), 2.51 (hept, J = 6.8 Hz, 2H, CCH(CH3)2), 2.03-1.93 (m, 2H, CH2 COD), 1.82-1.73 (m, 2H, CH2 COD), 1.62-1.57 (m, 2H, CH2 COD), 1.44 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.43 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.34-1.26 (m, 2H, CH2 COD), 1.29 (d, J = 6.8 Hz, 6H, CCH(CH3)2)), 1.10 (d, J = 6.8 Hz, 6H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] To a solution of HMDS (81 µL, 0.39 mmol, 1.4 equiv) in THF (5 mL) was added n-BuLi (1.6 M in hexane, 210 µL, 0.34 mmol, 1.2 equiv). The mixture was stirred at room temperature about 20 min. 1•H (135 mg, 0.28 mmol) was added as a solid and the solution was stirred for 20 minutes at room temperature. After cooling to -50°C, [AuCl(tht)] (90 mg, 0.28 mmol, 1 equiv), was added all at once and the reaction mixture was allowed to warm up to room temperature over 5 hours in the cooling bath. All volatiles were evaporated and the crude mixture was taken up in CH2Cl2 (5 mL) and iodobenzene dichloride (152 mg, 0.55 mmol, 2.0 equiv) was added. After 20 min, the orange solution was evaporated and purified by column chromatography (neutral Al2O3, Brockmann's type 3, CH2Cl2). All volatiles were removed in vacuo and crystallization by slow evaporation of CH2Cl2 (2 mL) overnight at room temperature led to two types of crystals with two different colors, dark-green and orange crystals. After manual separation and X-Ray analysis, green crystals were attributed to compound 9; 40 1 H NMR (400 MHz,CDCl3): δ = 7.72 (dd, J = 7.1, 1.2 Hz, 1H, CH Py), 7.62 (dd, J = 9.2, 1.1 Hz, 1H, CH Py), 7.49 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.47 (s, 1H, CH Im), 7.25-7.23 (m, 2H, CH m-Dipp), 7.14 (dd, J = 9.2, 7.2 Hz, 1H, CH Py), 5.04 (hept, J = 6.8 Hz, 2H, NCH(CH3)2), 2.10 (hept, J = 6.9 Hz, 2H, CCH(CH3)2), 1.59 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.43 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.24 (d, J = 6.8 Hz, 6H, CCH(CH3)2), 1.10 (d, J = 6.8 Hz, 6H, CCH(CH3)2); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] To a solution of HMDS (81 µL, 0.39 mmol, 1.4 equiv) in THF (5 mL) was added n-BuLi (1.6 M in hexane, 210 µL, 0.34 mmol, 1.2 equiv). The mixture was stirred at room temperature for 20 min. 1•H (135 mg, 0.28 mmol, 1 equiv) was added as a solid and the solution was stirred for 20 minutes at room temperature. After cooling to -50°C, [AuCl(tht)] (90 mg, 0.28 mmol, 1 equiv), was added all at once and the reaction mixture was allowed to warm up to room temperature over 5 hours in the cooling bath. All volatiles were evaporated and the crude mixture was taken up in CH2Cl2 (5 mL) and iodobenzene dichloride (152 mg, 0.55 mmol, 2.0 equiv) was added. After 20 min, dichloromethane was evaporated and the residue was purified by column chromatography (neutral Al2O3, Brockmann's type 3, CH2Cl2) to afford a mixture of complexes 9 and 10. In acetone-d6, based on the two singlets at H 8.20 ppm and H 8.35 ppm attributed respectively to the CHIm of the gold(III) complex 10 and CHIm of the gold(I) complex 9 protons, we were able to determine the ratio of the two gold complexes in the crude reaction mixture. The conversion of 9 to the thermodynamically more stable 10 occurred through successive crystallizations performed by slow evaporation of CH2Cl2 (2 mL) overnight at room temperature. The conversion was followed by 1 H NMR (CDCl3) after each crystallization. The gold(III) complex 10 was obtained as an orange powder (151 mg, 72 %); 1 H NMR (400 MHz, CDCl3): δ = 7.55 (t, J = 7.8 Hz, 1H, CH p-Dipp), 7.47 (d, J = 9.2 Hz, 1H, CH Py), 7.36 (s, 1H, CH Im), 7.30-7.27 (m, 3H, CH m-Dipp + CH Py), 6.73 (d, J = 6.8 Hz, 1H, CH Py), 5.09 (hept, J = 6.7 Hz, 2H, NCH(CH3)2), 2.19 (hept, J = 6.9 Hz, 2H, CCH(CH3)2), 1.51 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.48 (d, J = 6.9 Hz, 6H, NCH(CH3)2), 1.27 (d, J = 6.8 Hz, 6H, CCH(CH3)2), 1.13 (d, J = 6.8 Hz, 6H, CCH(CH3)2); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] n-BuLi (2.5 M in hexane, 373 µL, 0.933 mmol, 1.25 equiv) was added to a solution of HMDS (218 µL, 1.05 mmol, 1.4 equiv) in THF (25 mL) at room temperature and the reaction mixture was stirred for 20 minutes. 1•H (438 mg, 0.896 mmol, 1.2 equiv) was then added. The reaction mixture was stirred for another 20 minutes before the addition of [RuCl2(p-cymene)]2 (228 mg, 0.373 mmol, 0.5 equiv). The solution was stirred at room temperature overnight. The volatiles were removed under vacuum and the crude residue was purified by column chromatography (SiO2, eluent DCM/MeOH: 95/5) to give complex 11 as a deep orange powder (435 mg, 77%). 1 H NMR (400 MHz, CDCl37.59 (t, J = 7.7 Hz, 1H, CH p-Dipp), 7.41 (dd, J = 11.4, 7.8 Hz, 2H, CH m-Dipp), 7.13 (s, 1H, CH Im), 7.03 (d, J = 9.1 Hz, 1H, CH Py), 6.90 (dd, J = 9.2, 6.6 Hz, 1H, CH Py), 6.31 (d, J = 6.6 Hz, 1H, CH Py), 5.23 (hept, J = 6.9 Hz, 1H, NCH(CH3)2), 5.14 (br, 1H, C6H4 p-cym), 5.06 (d, J = 5.9 Hz, 2H, C6H4 p-cym), 4.85 (hept, J = 6.9 Hz, 1H, NCH(CH3)2), 4. 43-4.87 (br, 1H, C6H4 p-cym), 3.11 (hept, J = 6.6 Hz, 1H, CCH(CH3)2), 2.61-2.49 (m, 2H, CCH(CH3)2 + C6H4-CH(CH3)2), 1.75 (s, 3H, CH3 p- cym), 1.69 (d, J = 6.9 Hz, 3H, NCH(CH3)2), 1.55 (d, J = 6.9 Hz, 3H, NCH(CH3)2), 1.47 -1.42 (m, 9H, NCH(CH3)2 + CCH(CH3)2), 1.23 (d, J = 6.6 Hz, 6H, CCH(CH3)2), 1.03 (d, J = 7.1 Hz, 6H, CCH(CH3)2), 0.88 (d, J = 7.1 Hz, 3H, CCH(CH3)2)); [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] n-BuLi (2.5 M in hexane, 196 µL, 0.49 mmol, 1.2 equiv) was added to a solution of HMDS (120 µL, 0.58 mmol, 1.4 equiv) in THF (3 mL) at room temperature. After 20 min, 1•H (200 mg, 0.41 mmol, 1.0 equiv) was added. The mixture was stirred at room temperature for 20 min, and [MnBr(CO)5] (114 mg, 0.41 mmol, 1.0 equiv) was added. After stirring overnight at 60°C, all volatiles were removed under vacuum. The crude mixture was purified by column chromatography (neutral Al2O3 Brockmann type III, toluene) under a nitrogen atmosphere, washed with pentane (5 mL) and dried to give complex 10 as a greenish powder (100 mg, 37 %). Single crystals suitable for X-Ray diffraction experiment were obtained by slow evaporation of a solution of complex 10 in CHCl3. 1 H NMR (400 MHz, CDCl37.51 (t, J = 7.7 Hz, 1H, CH p-Dipp), 7.31 (d, J = 7.8 Hz, 2H, CH m-Dipp), 7.33-7.22 = 2083, 2004, 1992, 1954, 1714, 1653 : 655.1964; found: 655.1957, r = 1.1 ppm. Complex 12 was assessed to be >98% pure by 1 H and [START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectroscopy with main purity being residual CH2Cl2 (see the Supporting Information).

General screening procedure Ru-catalyzed dehydrogenative oxidation of primary alcohols

A stock solution of 11 (100 µL of a 9.3 mmol.L -1 solution in methylene chloride) was added to a Schlenk flask and methylene chloride was evaporated under high vacuum. Potassium hydroxide (1.2 equiv, 4.5 mmol, 252 mg), o-xylene (0.75 mL) and corresponding alcohol (3.75 mmol) were added, and a reflux condenser was set on top of the Schlenk flask. This latter was subsequently placed in a preheated oil bath at 150 °C. The mixture was stirred under reflux for 6 or 16 hours. The reaction mixture was cooled down to room temperature, water (4 mL) was added and the reaction mixture was stirred for additional 10 min. and sonicated if required to dissolve the carboxylate salt. The aqueous layer was then extracted with diethyl ether (3 x 20 mL) to remove unreacted alcohol. The water layer was acidified to pH = 2 using a 3N HCl solution and the carboxylic acid product was extracted with ethyl acetate (3 x 20 mL). The combined organic layers were dried over sodium sulfate, concentrated and dried under vacuum. Carboxylic acid 14f-i were purified Flash column chromatography (CombiFlash, SiO2, n-hexane/ethyl acetate gradient from 10 to 40 % as eluent).

Crystal Structure Determination

The crystals were kept in their mother liquor until they were dipped in perfluoropolyether oil and their structure determined. The chosen crystals were mounted on a MiTeGen MicroMount and quickly cooled down to either 100 K. The selected crystals were mounted on a Bruker Kappa APEX II using a micro-focus molybdenum Kα radiation (= 0.71073 Å) with a graphite monochromator and equipped with an Oxford Cryosystems Cooler Device. The unit cell determination and data integration were carried out using APEXII 41 . The structures have been solved by Direct Methods using SHELXS, [START_REF] Farrugia | WinGX suite for small-molecule single-crystal crystallography[END_REF] and refined by leastsquares procedures with SHELXL 43 included in the software packages WinGX version 1.63. [START_REF] Farrugia | WinGX suite for small-molecule single-crystal crystallography[END_REF] Atomic Scattering Factors were taken from the International Tables for X-Ray Crystallography. [START_REF]INTERNATIONAL tables for X-Ray crystallography[END_REF] Absorption correction was done using multi-scan DENZO/SCALEPACK (Otwinowski & Minor, 1997) method. [START_REF] Blessing | An empirical correction for absorption anisotropy[END_REF] All hydrogen atoms were geometrically placed and refined using a riding model.

All non-hydrogen atoms were anisotropically refined. Details of the structure solution and refinements are given in the Supporting Information (CIF file).

Figure 2 .

 2 Figure 2. Molecular structures of complexes 2, 3, 5, and 6. Ellipsoids are drawn at the 30% probability level. Hydrogen atoms have been omitted for clarity. Selected bond lengths and angles are reported in Table1.

30

 30

Figure 3 .

 3 Figure 3. Comparison of the νCO av stretching frequency values for Rh(I) complexes bearing chelating IPy-iminophosphorane, IPybarbituric heterocycle, and NHC-phosphonium ylide ligands, respectively.

Figure 4 .

 4 Figure 4. Molecular structures of complexes 9, 10, 11, and 12. Ellipsoids are drawn at the 30% probability level. Hydrogen atoms have been omitted for clarity. Selected bond lengths and angles are reported in Table2.

  C{ 1 H} NMR (101 MHz, CDCl3170.7 (N2C-Pd), 168.7 (CO), 165.8 (CO), 152.1 (CO), 146.2 (CAr), 145.5 (CAr), 141.4 (CPy), 136.6 (CAr), 131.3 (CPy), 130.3 (CHp-Dipp), 126.9 (CH Py), 123.8 (CH m-Dipp), 123.6 (CH m-Dipp), 116.9 (CH allyl), 114.3 (CH Py), 114.2 (CH Py), 110.9 (CH Im), 68.6 (CH2 allyl), 66.9 (Pd-C(CO)2), 53.0 (CH2 allyl), 45.6 (NCH(CH3)2), 45.4 (NCH(CH3)2), 28.2 (CCH(CH3)2), 28.1 (CCH(CH3)2), 25.3 (CCH(CH3)2), 24.4 (CCH(CH3)2), 24.2 (CCH(CH3)2), 23.6 (CCH(CH3)2), 20.8 (NCH(CH3)2), 20.6 (NCH(CH3)2), 19.8 (NCH(CH3)2), 19.5 (NCH(CH3)2); MS (ESI + ): m/z (%): 635.2 (49) [M + H] + (calcd 635.2), 489.3 (100) [M  Pdallyl +2H] + (calcd 489.3); Elemental analysis calcd (%) for C32H40N4O3Pd (MW = 635.11): C,

  C{ 1 H} NMR (101 MHz, CDCl3(d, 1 JC-Rh = 60.8 Hz, N2C-Rh), 165.9 (N-CO), 152.0 (N2CO), 145.8 (CDipp), 142.2(d, 2 JC-Rh = 1.7 Hz, C Py), 134.6 (Cipso-Dipp), 130.3 (CHp-Dipp), 130.2 (d, 3 JC-Rh =1.6 Hz, CPy), 126.6 (CHPy), 123.6 (CHm-Dipp), 113.8 (CHPy), 112.8 (CHPy), 111.3 (CHIm), 76.4 (d, 1 JC-Rh = 6.8 Hz, CHnbd), 69.8 (d, 1 JC-Rh =14.3 Hz, Rh-C(CO)2), 64.6 (d, 1 JC-Rh = 5.1 Hz, CH2 nbd), 59.0 (d, 1 JC-Rh = 10.4 Hz, CHnbd), 52.1 (d, 1 JC-Rh = 2.4 Hz, CHnbd), 45.6 (NCH(CH3)2), 28.2 (CCH(CH3)2), 26.4 (CCH(CH3)2), 23.3 (CCH(CH3)2), 21.2 (NCH(CH3)2), 20.2 (NCH(CH3)2); MS (ESI + ): m/z (%): 715.2 (25) [M  H + MeOH] + (calcd 715.2), 682 (100) [M] + (calcd 682.2); Elemental analysis calcd (%) for C36H43N4O3Rh (MW = 682.67) + 0.3 CH2Cl2: C,

  C{ 1 H} NMR (101 MHz, CDCl3167.8 (N-CO), (d, 1 JC-Rh = 55.2 Hz, N2C-Rh), 151.8 (N2CO), 145.7 (Co-Dipp), 143.3 (CPy), 135.0 (CDipp), 130.6 (CHp-Dipp), 130.5 (CPy), 126.4 (CHPy), 124.0 (CHm-Dipp), 113.6 (CHPy), 112.2 (CHPy), 112.1 (CHIm), 93.7 (d, 1 JC-Rh = 8.3 Hz, CHCOD), 75.5 (d, 1 =11.9 Hz, CHCOD), 68.8 (d, 1 JC-Rh =14.4 Hz, Rh-C(CO)2), 45.5 (NCH(CH3)2), 31.4 (CH2 COD) , 29.6 (CH2 COD), 28.3 (CCH(CH3)2), 26.4 (CCH(CH3)2), 23.0 (CCH(CH3)2), 20.8 (NCH(CH3)2), 20.1 (NCH(CH3)2); MS (ESI + ): m/z (%): 1419.6 (100) [2M  Na] + (calcd 1419.5), 721.7 (54) [M + Na] + (calcd 723.3); Elemental analysis calcd (%) for C37H47N4O3Rh (MW = 698.71) + 0.5 H2O: C, 62.79; H, 6.84; N, 7.92; found: C, 63.05; H, 6.61; N, 7.90 (water content in agreement with the integration of the 1

  C{ 1 H} NMR (101 MHz, CDCl3189.0 (d, 1 JC-Rh = 57.9 Hz, Rh-CO), 183.5 (d, 1 JC-Rh = 68.2 Hz, Rh-CO), (d, 1 JC-Rh = 49.0 Hz, N2C-Rh), 168.3 (d, 2 JC-Rh = 1.8 Hz, N-CO), 151.4 (N2CO), 146.1 (CDipp), 141.6 (CPy), 135.3 (Cipso-Dipp), 131.7 (CPy), 131.1 (CHp-Dipp), 127.5 (CHPy), 124.3 (CHm-Dipp), 114.5 (CHPy), 114.4 (CHPy), 111.8 (CHIm), 67.3 (d, 1 JC-Rh =15.8 Hz, Rh-C(CO)2), 46.6 (NCH(CH3)2), 28.4 (CCH(CH3)2), 25.0 (CCH(CH3)2), 24.2 (CCH(CH3)2), 20.5 (NCH(CH3)2), 19.6 (NCH(CH3)2); IR (CH2Cl2):  = 2069, 2010 cm -1 (C=O); MS (ESI + ): m/z (%): 673.

  C{ 1 H} NMR (101 MHz, CD2Cl2168.2 (N-CO), (N2C-Ir), 152.0 (N2CO), 146.2 (Co-Dipp), 145.2 (CPy), 135.5 (Cipso-Dipp), 131.1 (CHp-Dipp), 131.0 (CPy), 126.9 (CHPy), 124.5 (CHm-Dipp), 114.5 (CHPy), 114.0 (CHIm), 112.4 (CHPy), 80.1 (CHCOD), 70.6 (Ir-C(CO)2), 61.5 (CHCOD), 46.2 (NCH(CH3)2), 32.5 (CH2 COD) , 30.9 (CH2 COD), 28.8 (CCH(CH3)2), 26.5 (CCH(CH3)2), 23.1 (CCH(CH3)2), 21.1 (NCH(CH3)2), 20.1 (NCH(CH3)2); MS (ESI + ): m/z (%): 789.3 (100) [M  H] + (calcd 789.3); HRMS (ESI + ): m/z calcd.for C37H48N4O3Ir: 789.3356; found: 789.3338, r = 2.3 ppm. Complex 6 was assessed to be >98% pure by 1 H and[START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C NMR spectroscopy with main impurity being residual CH2Cl2 (see the Supporting Information).

  C{ 1 H} NMR (101 MHz, CDCl3): δ = 163.9 (N2C), 162.6 (N-CO), 150.0 (N2CO), 145.4 (C o-Dipp), 135.0 (C ipso-Dipp), 132.6 (C Py), 131.2 (CH p-Dipp), 129.7 (C Py), 124.4 (CH m- Dipp),122.9 (CH Py), 122.1 (CH Py), 120.1 (CH Py), 114.3 (CH Im), 64.2 (Cl-C(CO)2), 50.0 (NCH(CH3)2), 28.6 (CCH(CH3)2), 24.6 (CCH(CH3)2), 24.1 (CCH(CH3)2), 19.9 (NCH(CH3)2), 18.5 (NCH(CH3)2).

  C NMR (101 MHz, CDCl3): δ = 166.6 (N-CO-C), 150.5 (N2CO), 145.0 (C o-Dipp), 141.8 (N2C), 138.6 (C Py), 133.4 (C ipso-Dipp), 131.5 (CH p-Dipp), 130.5 (C Py), 128.5 (CH Py), 124.1 (CH m- Dipp), 116.1 (CH Py), 114.9 (CH Py), 114.5 (CH Im), 67.5 (Au-C(CO)2), 48.3 (NCH(CH3)2), 28.9 (CCH(CH3)2), 25.1 (CCH(CH3)2), 23.6 (CCH(CH3)2), 20.4 (NCH(CH3)2), 19.3 (NCH(CH3)2); MS (ESI + ): m/z (%): 809.2 (100) [M + MeOH + Na] + (calcd 809.2), 772 (62) [M + H + NH3] + (calcd 772.2), 760.2 (58) [M -Cl + CH3CN] + (calcd 760.2), 719.2 (28) [M -Cl] + (calcd 719.2); HRMS (ESI + ): m/z calcd. for C29H39AuCl2N5O3:772.2095; found: 772.2104, r = 1.2 ppm; Elemental analysis calcd (%) for C29H35AuCl2N4O3 (MW = 755.49) + 0.3 CH2Cl2:C 45.06, H 4.59, N 7.17; found: C 45.15, H 4.48, N 7.27 (despite considerable drying under high vacuum, CH2Cl2 could not be removed in totality from the sample).

  (m, 2H, CH Py + CH Im),7.10-7.04 (m, 1H, CH Py), 6.48(d, J = 6.7 Hz, 1H, CH Py), 5.16 (hept, J = 6.8 Hz, 2H, NCH(CH3)2), 2.36-2.31 (m, 2H, CCH(CH3)2), 1.51 (d, J = 6.8 Hz, 6H, NCH(CH3)2), 1.50 (d, J = 6.8 Hz, 6H, NCH(CH3)2), 1.26 (d, J = 6.8 Hz, 6H, CCH(CH3)2)), 1.09 (d, J = 6.8 Hz, 6H, CCH(CH3)2));[START_REF] Herbert | Z-Selective Cross Metathesis with Ruthenium Catalysts: Synthetic Applications and Mechanistic Implications[END_REF] C{ 1 H} NMR (101 MHz, CDCl3215.3 (Mn-CO), 214.2 (Mn-CO), 210.7 (Mn-CO), 173.7 (N-CO), (N2C-Mn), 151.0 (N2CO), 146.1 (CDipp), 141.7 (CPy), 135.0 (CDipp), 133.1 (CPy), 131.2 (CH p-Dipp), 126.8 (CH Py), 124.2 (CH m-Dipp), 116.0 (CH Im), 115.1 (CH Py), 114.6 (CH Py), 60.6 (Mn-C(CO)2) 46.4 (NCH(CH3)2), 28.4 (CCH(CH3)2), 26.8 (CCH(CH3)2), 22.5 (CCH(CH3)2), 20.4 (NCH(CH3)2), 19.6 (NCH(CH3)2); IR (CH2Cl2): 

Table

Table 1 . Selected bond lengths (Å) and angles (°) for the complexes 2, 3, 5, and 6.

 1

	2		3		5		6
	Pd1-C1	2.0191(19)	Rh1-C1	2.014(2)	Rh1-C1	2.0321(18)	Ir1-C1	2.032(3)
	Pd1-C8	2.2241(18)	Rh1-C8	2.269(2)	Rh1-C8	2.2281(19)	Ir1-C8	2.232(3)
	Pd1-C30	2.181(2)	Rh1-C30	2.139(2)	Rh1-C30	1.899(2)	Ir1-C32	2.174(3)
	Pd1-C31B	2.148(6)	Rh1-C31	2.115(2)	Rh1-C31	1.864(2)	Ir1-C33	2.148(4)
	Pd1-C32	2.138(2)	Rh1-C33	2.182(2)	C11-O2	1.217(2)	Ir1-C36	2.131(4)
	C8-C9	1.463(3)	Rh1-C34	2.209(2)	C9-O1	1.221(2)	Ir1-C37	2.126(4)
	C8-C11	1.467(3)			C31-O31	1.134(3)	C32-C33	1.390(6)
	C9-O1	1.224(2)			C30-O30	1.134(3)	C36-C37	1.400(6)
	C11-O2	1.221(2)
	N1-C1-N2	103.52(16)	N1-C1-N2	102.79(19)	N1-C1-N2	103.50(15)	N1-C1-N2	102.8(3)
	C1-Pd1-C8	81.33(7)	C1-Rh1-C8	79.41(9)	C1-Rh1-C8	80.12(7)	C1-Ir1-C8	79.02(13)
	Yaw angle 	13.94	Yaw angle 	12.70	Yaw angle 	13.22	Yaw angle 	14.05
	C8	344.86	C8	344.80	C8	341.21	C8	340.3
	= [(N1-C1-M)-(N2-C1-M)]/2

Table 2 . 13 C NMR chemical shifts for the carbenic and cen- tral malonic atoms recorded in CDCl3.

 2

	Compound	(Ccarbene) (ppm)	(Cmalo) (ppm)
	1•H	127.2	83.3
	1•Li [a]	199.2	88.2

Table 3 . Selected bond lengths (Å) and angles (°) for the complexes 9, 10, 11, and 12.

 3

	9		10		11		12
	Au1-C1	1.979(2)	Au1-C1	1.9932(19)	Ru1-C1	2.035(4)	Mn1-C1	2.0200(15)
	Au1-Cl1	2.2850(6)	Au1-C8	2.1319(19)	Ru1-C8	2.316(4)	Mn1-C8	2.2907(15)
	C8-Cl2	1.817(2)	Au1-Cl1	2.3076(5)	Ru1-Cl1	2.3992(12)	Mn1-C30	1.8632(18)
			Au1-Cl2	2.3336(5)			Mn1-C31	1.8278(16)
							Mn1-C32	1.8715(17)
							Mn1-C33	1.8230(17)
	N1-C1-N2	104.50(18)	N1-C1-N2	105.03(16)	N1-C1-N2	103.2(4)	N1-C1-N2	103.35(12)
	C1-Au1-Cl1	177.64(7)	C1-Au1-C8	82.55(7)	C1-Ru1-C8	77.43(17)	C1-Mn1-C8	79.61(6)
	Yaw angle 	-6.56	Yaw angle 	14.10	Yaw angle 	10.80	Yaw angle 	12.22
	C8	341.46	C8	338.21	C8	336.1	C8	339.44

Table 4 . Ruthenium-catalyzed dehydrogenative oxidation of benzyl alcohol. Optimization of the reaction conditions. a

 4

				NMR
	Entry	Cat. (ppm)	Time (h)	yield	TON
				(%) b
	1	11 (250)	2	88 c	3500
	2	11 (250)	5	96 c	3800
	3	11 (250)	0.5	36	1400
	4	11 (250)	1	61	2400
	5	11 (250)	1.5	72	2900
	6	11 (250)	2	87	3500
	7	11 (250)	2.5	98	3900
	8	11 (250)	3	>99	>4000
	9	11 (25)	13	65	26000
	10	11 (25)	24	76	30400
	11	11 (10)	24	33	33000
	12	11 (10)	48	73	73000
	13	-	5	0.4
	14	[RuCl2(p-cym)]2	6	9	180
		(250)

a Typical conditions: benzyl alcohol (7.5 mmol), potassium hydroxide (1.2 equiv), o-xylene (1.4 mL ) under an open air atmos-

  cm -1 (C=O); MS (ESI + ): m/z (%): 655.2 (18) [M H] + (calcd 655.2), 649.2 (24) [M CO a] + (calcd 649.2), 627.2 (100) [M CO H] + (calcd 627.2), 584.2 (90) [M CO CCN + H] + (calcd 584.2), 575.2 (85) [M CO MeOH + H] + (calcd 575.2), 543.2 (79) [M CO H] + (calcd 543.2), 489.3 (48) [M nCO+ H] + (calcd 489.3); HRMS (ESI + ): m/z calcd. for C33H36N4O7Mn

ACKNOWLEDGMENT

This work was supported by the Agence Nationale de la Recherche (ANR-16-CE07-0006), the Centre National de la Recherche Scientifique (CNRS) and the University Côte d'Azur. I.B. is grateful to ANR for PhD grants and K.G. to the French government for part of a PhD grant.

ASSOCIATED CONTENT Supporting Information

The Supporting Information is available free of charge on the ACS Publications website.

NMR spectra and characterization of the products of catalysis (PDF) Crystallographic data (CIF)

Accession Codes

CCDC 2085777-2085784 contain the supplementary crystallographic data for this paper. These data can be obtained free of charge via www.ccdc.cam.ac.uk/data_request/cif, or by emailing data_request@ccdc.cam.ac.uk, or by contacting The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK; fax: +44 1223 336033.

AUTHOR INFORMATION

Corresponding Author * E-mail for V.C.: vincent.cesar@lcc-toulouse.fr * E-mail for S.B.: stephanie.bastin@lcc-toulouse.fr

Notes

The authors declare no competing financial interest.