Thomas Romera
email: thomas.romera@lip6.fr

Alexandre Brière
email: alexandre.briere@esiea.fr

Julien Denoulet
email: julien.denoulet@lip6.fr

Dynamically Reconfigurable RF-NoC with Distance-Aware Routing Algorithm

Keywords: Integrated circuit interconnections, Network on Chip, NoC, Radio Frequency, RF, Dynamically Reconfigurable, Multi-Core, Many-Core

With the growing number of cores per processor, onchip communications are becoming a critical issue. Conventional wired mesh Networks-on-Chips (NoC) are reaching their scalability limit, paving the way for new interconnect technologies such as Radio Frequency (RF), Optics and 3D. This paper presents a new routing mechanism based on the WiNoCoD architecture, a hierarchical RF interconnect with dynamic bandwidth allocation for Chip Multi Processors (CMP). WiNoCoD consists of three levels of hierarchy with an RF NoC at the highest level, a wired mesh NoC and a crossbar at the lowest level. In this paper, we propose a new organisation for the manycore supporting the RF-NoC, and introduce a new routing algorithm that can choose between wired and RF networks in order to optimize the use of RF. We show that the new architecture improves performance in terms of latency and saturation. Platform simulations show a latency reduction for lower transaction rates of up to 10% compared to the original WiNoCoD architecture and up to 30% compared to a wired mesh NoC. Furthermore, smart routing pushes back the saturation threshold up to 20%.

I. INTRODUCTION

Conventional Network-on-Chips (NoCs) are interconnects using routers linked together to form a grid and used to connect processor nodes inside a chip. They have been developed to resolve communication issues that classical communication mediums, such as bus and crossbar, present in the context of Chip Multi Processors (CMP). Indeed, bus interconnects have latency issues when too many initiators want access for communications. Furthermore, physical limitations such as wire length and clock frequency limit the bandwidth of the bus. Crossbars improve latency and bandwidth at the cost of a lot more chip surface dedicated to the interconnect. Moreover, the bandwidth grows with the size of the network, even if the maximum length of the wires used to connect the routers can have an impact on the topology of the network.

However, in conventional NoCs, latency limitations arise when the number of cores increases: the further two cores are apart, the more intermediate routers will have to be crossed by transmitted data to reach the destination. Additionally, wired mesh networks are not particularly suited for broadcast type transactions and dynamic reconfiguration.

Technological solutions such as 3D, Optics and Radio Frequency (RF) are being developed to alleviate those issues.

In [START_REF] Drillet | Flexible Radio Interface for NoC RF-Interconnect[END_REF], we introduced the WiNoCoD architecture (Wired RFbased Network On Chip Reconfigurable On Demand) as an RF solution using a hierarchical RF NoC with dynamic allocation of communication resources.

In this paper, we present a new routing mechanism for the WiNoCoD architecture. It is based on a new organisation of the manycore supporting the RF-NoC and introduces a routing mechanism that chooses between the RF and the wired networks, according to the distances between sources and destinations. The rest of the paper is organised as follows. Section 2 presents an overview of related works. Section 3 presents the RF NoC architecture. In order to evaluate our new solution, section 4 details the experimental setup used to evaluate the RF NoC, and section 5 presents and analyses the obtained results. Finally, section 6 concludes the paper.

II. RELATED WORKS

Following ITRS recommendations [START_REF] Itrs | International Technology Roadmap for Semiconductors[END_REF], new technologies are being explored to solve intra-chip communication issues such as latency and bandwidth. 3D solutions try to reduce distances while optic and RF solutions try to reduce transit time. Furthermore, architectural solutions are explored to optimize the use of communication resources thanks to dynamic allocation.

A. Technological Solutions 1) 3D NoC: With 3D chips, stacked layers are used to increase the connectivity of the NoC routers. Vertical connections are added between layers and can be used to transmit data [START_REF] Banerjee | 3-D ICs: A novel chip design for improving deep-submicrometer interconnect performance and systems-on-chip integration[END_REF]. By switching from a large 2D chip to several smaller stacked layers, the maximum distance between two nodes in a network of size N is reduced from 2

√

N to 3 √ N . This type of connection can also be used to connect specialised layers in heterogeneous System-on-Chip (SoC). However, larger 3D NoCs encounter the same problems as 2D NoCs in terms of latency and saturation. Mixed systems using 3D and optics [START_REF] Ye | 3D optical Networks-on-Chip (NoC) for Multi-Processor Systems-on-Chip (MP-SoC)[END_REF] or 3D and RF [START_REF] Lee | 3D Networkon-Chip with Wireless Links through Inductive Coupling[END_REF] aim to solve those problems. Nevertheless, heat dissipation remains a problem in 3D architectures [START_REF] Esmaeilzadeh | Power Challenges May End the Multicore Era[END_REF].

2) Optical NoC: Optical NoCs allow for much greater transmission speed than regular wired NoCs [START_REF] O'connor | On-Chip Optical Interconnect for Low-Power[END_REF]. They are composed of emitters that convert electrical signals into optical ones; a physical optical guide where optical waves travel; receivers that translate optical waves into electrical signals [START_REF] Kurian | ATAC: A 1000-Core Cache-Coherent Processor with On-Chip Optical Network[END_REF]. If these NoCs allow for greater bandwidth and lower latency, they can require different semi-conductor technologies than CMOS. Furthermore, they suffer from greater thermal sensitivity and typically require an external light source.

Waveguide

3) RF NoC: Similar to optical NoCs, RF NoCs enable faster communication to solve bandwidth and latency problems [START_REF] Chang | RF/Wireless Interconnect for Inter-and Intra-Chip Communications[END_REF]. However, they have the benefit of being fully compatible with current CMOS technologies. Radio waves can be transmitted using a waveguide [START_REF] Chang | CMP Network-on-Chip Overlaid With Multi-Band RF-Interconnect[END_REF] or antennas [START_REF] Deb | CMOS Compatible Many-Core NoC Architectures with Multi-Channel Millimeter-Wave Wireless Links[END_REF]. Architectures using antennas are more flexible than those using waveguides but suffer from more sensitivity to interference and increased power consumption [START_REF] Karkar | A Survey of Emerging Interconnects for On-Chip Efficient Multicast and Broadcast in Many-Cores[END_REF].

B. Communication Resources Allocation

The above technological solutions aim to improve both latency and bandwidth. However, on-chip traffic is not necessarily constant and uniform in both space and time. Dealing with this spatio-temporal heterogeneity is one of the major limitations of classical wired NoCs. Adding priority to some messages does not remove the obligation to travel through intermediate routers for node-to-node communication. Moreover, reassigning unused bandwidth to parts of the chip that need it is a complex task on both 2D and 3D wired NoCs.

However, both optical and RF NoCs can establish direct communication links between any source and destination on the chip. Overlying such network on top of a classical NoC allows to create shortcuts thanks to the physical medium (waveguide, antennas, frequency bands, etc.) of this top-level network. Moreover, this extra bandwidth can be dynamically reallocated to handle heterogeneous traffic. Therefore, three types of allocation mechanisms have been proposed: Multiple Write Single Read (MWSR), Single Write Multiple Read (SWMR) and Multiple Write Multiple Read (MWMR).

Indeed, in optical and RF NoCs, the bandwidth is divided in channels that can be allocated according to the communication needs of the nodes. In [START_REF] Vantrease | Corona: System Implications of Emerging Nanophotonic Technology[END_REF], an MWSR communication scheme is presented where each receiver node has an associated channel used to receive data from other nodes. However, MWSR does not support broadcast and requires additional logic to avoid data collision from multiple sources writing to the same destination.

In [START_REF] Kurian | ATAC: A 1000-Core Cache-Coherent Processor with On-Chip Optical Network[END_REF], an SWMR scheme is implemented. Each channel is used by a single emitter node to communicate. Each receiver node has to decode every channel to identify the data intended for it. SWMR supports broadcasting but requires more power as a node writes on all available channels.

The MWMR scheme allows for multiple channels to be assigned to a single node for transmitting while simultaneously allowing for each node to receive data from different channels and nodes [START_REF] Xiao | Stream Arbitration: Towards Efficient Bandwidth Utilization for Emerging On-Chip Interconnects[END_REF]. This scheme requires arbitration on both emission and reception and consumes the most energy. However, it is the most flexible scheme, allowing for advanced reconfiguration mechanisms and supports broadcast.

III. PROPOSED ARCHITECTURE

As said in the previous section, RF communication has a number of advantages, especially in terms of propagation time, which is about 0.5 ns for 100 mm in silicon. At the scale of a chip, it can be considered constant regardless of source and destination. Furthermore, RF waves transmission and reception times are also constant for every source and destination. This means an RF NoC is able to transmit data in constant time, unlike router-based NoCs where delay increases along with the distance between source and destination. Still, even if constant, this time is greater than the one required to cross a single router. It is then relevant to use the RF NoC only from a certain distance of transmission. Another benefit of using RF communication is the ability to dynamically allocate communication resources in order to maximise bandwidth occupation.

The WiNoCoD hierarchical architecture has therefore been set up, with the RF NoC as the highest communication level. In [START_REF] Brière | A Dynamically Reconfigurable RF NoC for Many-Core[END_REF], we evaluated the physical characteristics of WiNoCoD for a CMP with 4 096 cores assuming a 22 nm target technology. The complete RF NoC contributes to 5.5% of the overall power consumption which is 180 W, and 4.5% of the overall area which is 920 mm 2 . Those overall physical characteristics being comparable with those of the IBM POWER8 which are 190 W and 649 mm 2 .

In this section, we first describe the WiNoCoD architecture and then detail changes proposed to allow optimization of the use of communication resources. We then focus on communication management itself within the architecture, first presenting the RF channels allocation algorithm, then focusing on the new smart routing mechanism that aims to judiciously dispatch data between the wired and the RF networks.

A. CMP Architecture and RF-NoC Interface

The hierarchical architecture of the CMP used in WiNoCoD is composed of super-clusters which contain clusters, which themselves contain multiple cores and various peripherals as shown in Fig. 1.

The first level in the hierarchy is the cluster. A cluster contains P processors, each with an instruction and a data cache, along with a local RAM and a DMA. These components are connected with a crossbar that can access a grid-router, allowing inter-cluster communications on the second hierarchy level. The second level is the super-cluster. A cluster is connected to four of its neighbours to form a M ×M grid. One router in each super-cluster (typically the one at the center) is connected to the RF waveguide using a specialised RF interface. The third and final level is the RF NoC. It is used to connect the different super-clusters together via the waveguide using the RF interface. The waveguide is the structure that supports radio-waves transmission from emitter to receiver.

Within this scheme, two types of organisations have been defined and tested, the original strict version [START_REF] Brière | A Dynamically Reconfigurable RF NoC for Many-Core[END_REF] and a new flexible one which we introduce in this work:

1) Strict CMP Hierarchy: In the original strict organisation, super-clusters can only communicate using the RF NoC through the waveguide, as shown in Fig. 1. This has the advantage of simplifying routing since there is only one path between two clusters in different super-clusters: the RF waveguide. However, this topology increases the latency between physically neighbouring clusters when they are located in different super-clusters: indeed, they have to pass across the CMP using RF, which has a higher transmission time than crossing a single router. Furthermore, this organisation increases the number of communications through the RF NoC, which may artificially create bottlenecks in the network and therefore increase global latency.

2) Supple CMP Hierarchy: We introduce a new organisation, pictured in Fig. 2. The supple hierarchy adds wired connections between adjacent clusters in different super-clusters. A 2D-mesh that spans the entire CMP is thus created and data can now travel either as if it was on a classical wired NoC mesh or by using the RF waveguide. However, the routers of the clusters now have to decide between routing data using the wired mesh or using the RF NoC. This is achieved by modifying the router and adding time and distance Fig. 2. Supple CMP hierarchical architecture considerations between the emitter and the receiver on the mesh, at the cost of more hardware complexity.

3) RF NoC Interface Architecture: In both strict and supple organisations, each cluster features an RF interface that allows access to the waveguide (see Fig. 3). The interface translates data packets coming from the wired network into radio waves. The RF NoC uses Orthogonal Frequency Division Multiple Access (OFDMA) to encode data. This type of scheme splits the bandwidth into sub-channels that can be assigned and reassigned to the various super-clusters using a dynamic bandwidth allocation algorithm. It allows multiple super-clusters to simultaneously transmit on the different sub-channels of the bandwidth, depending on their needs. The RF interface converts the flow units (flits) into RF signals and its main components are:

1) An arbiter that queues data flits coming from the wired network and translates them into flits that will circulate on the RF network. It also send the filling state of its internal FIFO which is used in the dynamic allocation algorithm. 2) A coder handles data encoding into symbols using BPSK, QPSK or 16-QAM modulation schemes. 3) A demultiplexer performs the placement of data symbols corresponding to the allocated sub-channels of the RF bandwidth and the filling state symbols on the dedicated service sub-channel of the super-cluster. 4) An N -point IFFT produces the real and imaginary parts of the signal to be sent, with N the sub-channels total number. 5) An emitter that converts the IFFT outputs from digital domain to analog domain and then sends the signal on the waveguide. 6) The waveguide. ) A receiver that collects the signal sent on the waveguide and then converts it back in the digital domain. 8) An N -point FFT that divides the signal into the N original sub-carriers. 9) A multiplexer that reconstructs the emitted data flits and the service flit by selecting symbols on sub-channels of the bandwidth. 10) A decoder that decodes data according to the chosen modulation schemes. 11) A router that transmits data flits to the wired network, only if the flit is intended for the given super-cluster, and the service flit to the RF controller. 12) An RF controller that implements the dynamic allocation algorithm. To do so, it receives the filling state information of all the clusters thanks to the dedicated service sub-channel of the RF bandwidth. It also indicates to the demultiplexer which sub-channels are available to send data and to the coder and the decoder which modulation scheme is currently used according to the allocation algorithm.

B. Communications Resources Management

Routing in the wired network is performed using a Xfirst algorithm: routing is first done in the X dimension and once the correct column is reached, the packet is vertically routed in the Y dimension. This routing is deadlock-free since restrictions on data routing prevents circular dependencies in routers. In this subsection, we detail how the RF interface dynamically allocates RF channels to super-clusters. In order to limit the saturation of the RF network and optimize the use of RF, we then introduce the routing mechanism that chooses between the two networks.

1) RF Dynamic Bandwidth Algorithm: In order to optimize the bandwidth utilisation, a dynamic allocation algorithm was devised exploiting the OFDMA reconfiguration potential [START_REF] Brière | A Dynamically Reconfigurable RF NoC for Many-Core[END_REF]. This algorithm is distributed in all the RF controllers to avoid latency and extra communications between RF interfaces. To do so, each super-cluster must periodically transmit its filling state using its dedicated part of the service sub-channel of the RF NoC. Thanks to the architecture's intrinsic broadcast support, sending this information to all the nodes takes the same effort as sending them to a single node.

The dynamic allocation algorithm is divided into four states (see Fig. 4):

1) At the start of the RF cycle t, each super-cluster i sends its filling state B t i on the RF-NoC. The RF controllers then collect all the emitted filling states.

2) The controllers compute the sum S t of the filling states B t i of all the N super-clusters connected to the waveguide:

S t = N j=1 B t j .
3) The controllers then compute A t+1 i , the number of subchannels to be allocated to node i at cycle t + 1, with M the total number of sub-channels:

A t+1 i = M × B t i S t
4) The allocated sub-channels are then registered in the demultiplexer. They can now be used by the supercluster to transmit data through the RF NoC. Data can be continuously transmitted over the RF network, even while the controller computes a new allocation configuration. When computation is finished, the new available subchannels are simply provided to the demultiplexer. 2) Smart Routing: The new supple architecture requires a routing algorithm that chooses between the wired and the RF networks. In order to do so, we developed a routing algorithm which estimates the routing time between the current router and the destination. It takes A cycles to cross a single router and B cycles to cross the RF NoC. So, to go from a local node (x l , y l ) to a destination node (x d , y d ) using only the wired NoC, you need the following number of cycles t N oC :

t N oC = A × (| x d -x l | + | y d -y l |) (1)
To travel using the RF NoC, the algorithm first routes the flit from the local cluster (x l , y l ) to the local RF interface cluster

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3,25 20

3 3 3 3 2 2 2 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 2 2 2 2 2 2
3,63 (x l RF , y l RF ) using the wired network. The flit then travels through the waveguide to the destination super-cluster. It is received by the destination RF interface cluster (x d RF , y d RF ).

21 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 4,00 22
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Finally, it is routed to the destination cluster (x d , y d ) using the wired network. We therefore need to add these three transmission times to obtain the total number of cycles t RF to pass through the RF:

t RF = A × (| x l RF -x l | + | y l RF -y l |) + B + A × (| x d -x d RF | + | y d -y d RF |) (2)
If the cycle number t N oC is less than or equal to t RF , the routing will be done over the wired network and otherwise over the RF network. Without smart routing and for homogeneous traffic, a packet is ×15 more likely to use RF over the wired network, thus probably creating saturation issues. Smart routing allows to level out this ratio, as can be seen on Fig. 5, which shows the ratio between packets using RF and packets using only the wired network. As found by simulation, the maximum ratio is now 4. Clusters on the edges of the chip, or at the center of super-clusters are more likely to require long distance transmission. Therefore, smart routing grants them a better access to the RF NoC.

IV. EXPERIMENTAL METHODOLOGY

In order to simulate the WiNoCoD architecture, test platforms were modelled in SystemC CABA (Cycle Accurate -Bit Accurate) using the SoCLib library of components [START_REF]Soclib Documentation[END_REF]. We aimed to evaluate the new supple organisation and measure the impact of the communication resources optimization features: dynamic RF bandwidth allocation and smart routing between RF and wired networks. To do so, the models must provide the RF bandwidth distribution among the super-clusters, and also represent data travelling on these RF channels. In the RF-NoC interface architecture, on the emitter side, this information is available at the output of the demultiplexer stage (or at the input of the multiplexer stage on the receiver side). As a result, for simulation speed purposes, we chose for our models to abstract the RF front-end and the waveguide, therefore, in our platforms, an "ideal digital waveguide" connects the RF interfaces demultiplexers with the multiplexers. More information about the RF front end and its performances can be found in [START_REF] Hamieh | Sizing of the Physical Layer of a RF Intra-Chip Communications[END_REF].

Another simplification was the substitution of CPU cores inside the cluster with traffic generators. Four kinds of traffics were tested on the architectures:

• Homogeneous traffic (Fig. 6) in which a cluster sends a transaction to another randomly chosen cluster. • Heterogeneous traffic (Fig. 7) in which all clusters send transactions to the same cluster thus creating a hot-spot. • Broadcast traffic (Fig. 8) in which all the clusters can generate broadcast type transactions. • Mixed traffic (Fig. 9) which aims to approximate the overall traffic of real applications. It is composed of 5% of broadcasts, 10% of heterogeneous transactions and 85% of homogeneous traffic. These average rates have been estimated by Jerger et al. [START_REF] Jerger | Virtual Circuit Tree Multicasting: A Case for On-Chip Hardware Multicast Support[END_REF] for broadcast and Chiu et al. [START_REF] Chiu | The odd-even turn model for adaptive routing[END_REF] for hot-spots. A version of WiNoCoD was written using the Distributed Scalable Programmable Interconnect Network (DSPIN) [START_REF] Panades | A Low Cost Networkon-Chip with Guaranteed Service Well Suited to the GALS Approach[END_REF]. This router network is already described using SoClib and thus provides the 2D mesh framework needed by WiNoCoD. The DSPIN routers were modified and a new communication port was added in order to route data toward the RF network. Note that it is also possible to interface WiNoCoD with different protocols in order to be linked with different sets of IP cores.

For the experimental parameters, we chose to simulate three different architectures, each featuring 1 024 clusters:

• A 2D 32 × 32 mesh NoC based on DSPIN routers, • A strict WiNoCoD architecture of 16 super-clusters, each including 8 × 8 clusters, with and without dynamic reconfiguration, • A supple WiNoCoD architecture of 32×32 clusters, with and without dynamic reconfiguration. The number of cycles to cross a single DSPIN router was set to A = 3 since their finite-state machines include 3 states. The number of cycles to cross the waveguide depends on the bandwidth characteristics and the CPU core frequency. We assume a bandwidth of 20 GHz divided into 512 sub-carriers and cores running at 1 GHz which induces B = 25 cycles to cross the RF NoC [START_REF] Hamieh | Sizing of the Physical Layer of a RF Intra-Chip Communications[END_REF].

V. RESULTS ANALYSIS

At this point, we need to carefully distinguish "RF-cycles", corresponding to the OFDMA period of 25 ns and used to represent the injection rate, from "cycles" corresponding to the 1 Ghz clock frequency of the cores and used to evaluate the latency of communications. Fig. 6 shows that the wired mesh network has a constant latency of 139 cycles for injection rate up to 1 transaction per cluster per RF-cycle. The mesh saturation is not shown on the graph, the saturation occurring for injection rates around 4 transaction/cluster/RF-cycle. The strict WiNoCoD architecture starts out with a latency 10% lower at 127 cycles for lower injection rates. It saturates for injection rates of about 0.5 transaction/cluster/RF-cycle. The supple WiNoCoD architecture has a latency 18% lower than that of the wired mesh at 114 cycles also for lower injection rates.

The following results highlight the two main characteristics of WiNoCoD: the RF NoC and the dynamic reconfiguration. With the RF NoC, latency improvements are achieved for all traffic types at low injection rates. In particular, Fig. 8 shows that thanks to OFDMA, the latency of broadcast transactions is decreased by 36%, from an average of 159 cycles on the DSPIN architecture to 101 cycles for the WiNoCoD architectures. For heterogeneous traffic and low injection rates, Fig. 7 shows a 30% improvement in latency between the DSPIN architecture and both WiNoCoD architectures. For homogeneous and mixed traffic, latency for low injection rates is reduced by 9% and 13% respectively as shown in Fig. 6 and Fig. 9 respectively.

Additionally, the new smart routing scheme is able to further reduce latency by dispatching data in a more optimized way between the wired and the RF networks. For homogeneous traffic and low injection rates, Fig. 6 shows that latency decreases by 10% between the original strict architecture and the new supple one, from 127 cycles to 114 cycles, for homogeneous traffic. For mixed traffic and low injection rates, Fig. 9. Communications latency for mixed traffic Fig. 9 shows a 20% reduction in latency between the strict architecture and the supple one. Furthermore, the new routing scheme pushes back the saturation threshold. Fig. 6 shows that the saturation point is pushed back by 30%, from an injection rate of 0.5 transaction/cluster/cycle to 0.65. The same effect can be seen in Fig. 9, the saturation point goes from 0.5 for the strict architecture to 0.6 for the supple. Overall, comparing the strict and supple architectures, both using dynamic bandwidth allocation, we see that the saturation threshold is pushed back by 20%.

As for smart routing, the RF dynamic allocation algorithm benefits vary with the type of generated traffic. For example, in Fig. 8, comparisons between static and dynamic versions of the architecture show that RF bandwidth reconfiguration does not improve performances for broadcast. However, for others traffics such as heterogeneous traffic, Fig. 7 shows that dynamic reconfiguration allows to greatly improve the saturation issue, as it goes from an injection rate of 0.05 for static configurations to 0.4 for the dynamic ones.

In the end, for mixed traffic, Fig. 9 shows that dynamic reconfiguration allows to push back the saturation threshold. With the strict architecture, it is improved by up to 43% compared to a fixed allocation of the RF channels. The saturation point goes from 0.35 to 0.5. With the supple architecture, the saturation point is improved by up to 50%, from 0.4 with a static configuration to 0.6 with a dynamic allocation.

Finally, comparing WiNoCoD with the DSPIN architecture, Fig. 9 shows that on one hand, the supple WiNoCoD architecture outperforms DSPIN for injection rates up to 0.45. On the other hand, the saturation threshold for DSPIN occurs at a higher rate than WiNoCoD. However, the conducted experiments only take into account a limited spatial and temporal communication heterogeneity, since all clusters follow the same behavior throughout simulation duration. This would not necessarily be the case if we were to run real software applications. So, it would be interesting to run such experiments to evaluate up to which point WiNoCoD's lower saturation threshold is penalising.

VI. CONCLUSION

This paper proposed a new routing mechanism for the WiNoCoD architecture and studied its impact in terms of latency and saturation. A new, more flexible architecture with smarter transaction routing has been defined. In order to compare our new architecture with the original WiNoCoD architecture and with a more conventional wired NoC, Sys-temC models of platforms have been developed. We studied a CMP with 1 024 clusters in which the RF NoC represents 5.5% of the overall power consumption and 4.5% of the overall area of the chip. Simulations were performed using synthetic traffic generators with several profiles: homogeneous, heterogeneous, broadcast and mixed. For homogeneous traffic, the new, more flexible architecture allows to improve latency by up to 10% compared to the original strict architecture and up to 30% compared to a wired 2D NoC architecture based on DSPIN routers. For mixed traffic, latency is decreased by 20% between the strict architecture and the new supple one. The supple WiNoCoD architecture also allows to push back the saturation threshold by 20% compared to the strict architecture. Future work aims at refining the routing algorithm by including other parameters such as RF and wired networks saturation consideration, in order to further optimize the use of the RF NoC. Work is also being carried out to test real software on the architecture to evaluate and compare more precisely our improvements.

ChipFig. 1 .

 1 Fig. 1. Strict CMP hierarchical architecture

Fig. 3 .

 3 Fig. 3. Functional diagram of the RF interface

Fig. 4 .

 4 Fig. 4. RF controller allocation scheme timing diagram

Fig. 7 .

 7 Fig. 7. Communications latency for heterogeneous traffic

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 X Y

  Fig. 5. Ratio of use between RF and wires for each cluster.

																							2	1	1	2	2	3	3	3	3	3	3
	28	4	4	4	4	3	3	3	2	2	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	2	3	3	3	3	3	3	3
	29	4	4	4	4	3	3	2	2	2	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	2	3	3	3	3	3	3	3
	30	4	4	4	4	3	3	2	2	2	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	2	2	3	3	3	3	3	3
	31	3	3	4	4	3	3	2	2	2	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	2	2	3	3	3	3	3	3
	32	3	3	3	3	3	3	2	2	2	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	2	2	3	3	3	3	3	3
		1 2 3 4 5 6 7 8


Julie Coloigner

Anne-Claire Binter

Elise Bannier

Jean-Christophe Ferré

Cécile Chevrier

Christian Barillot

Fabienne Pelé

EFFECT OF PRENATAL ORGANIC SOLVENT EXPOSURE ON STRUCTURAL CONNECTIVITY AT CHILDHOOD

Keywords: diffusion-weighted imaging, graph theory, diffusion, organic solvents, brain development

Glycol ethers are part of organic solvents. They are used in industry and at home during manufacturing or usage of products such as paints, cleaning agents and cosmetics. The specific detection of subtle, low-dose effects of early-life exposure to these solvents on neuropsychological performance in children is a trendy subject of investigation. Neuroimaging allows looking into brain function and identifying different cerebral connections that may be affected by these neurotoxicants. In this paper, we investigated the specific effects of prenatal low-level exposure to different glycol ethers, on brain development of children between 10 and 12 years old. Based on previous studies suggesting cognitive disabilities in the attention, inhibition and working memory, we proposed a structural connectivity analysis using graph theory restricted to the regions involved in these functions. Our results suggest a possible relationship between the attention, working memory and inhibition and prenatal exposure to specific glycol ethers, such as ethoxyacetic acid, ethoxyethoxyacetic acid and 2-butoxyacetic acid.

INTRODUCTION

Glycol ethers are part of organic solvents. They are used in industry and the home during manufacturing or usage of products such as paints, cleaning agents and cosmetics. Pregnant women are ubiquitously exposed to organic solvents and more particularly glycol ethers according to French and European biomonitoring data [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF]. The neurotoxicity of glycol ethers is recognized in adults [START_REF] Pomierny | Potential neurotoxic effect of ethylene glycol ethers mixtures[END_REF]. And these substances are able to cross the blood brain barrier [START_REF] Grandjean | Developmental neurotoxicity of industrial chemicals[END_REF], which may interfere directly in neurological brain development [START_REF] Barbosa | Exposure to organic solvents used in dry cleaning reduces low and high level visual function[END_REF], raising particular concern. Specific effects of prenatal exposure to glycol ether on child neurodevelopment have been poorly studied. Only one epidemiological study investigated the specific effects of prenatal exposure to glycol ethers on neurodevelopment. Authors report that 6-year old children with the higher level of in-utero exposure to glycol ethers had lower verbal comprehension and copying score [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF]. However, converging evidence shows an association between prenatal exposures to organic solvents in general and child neurodevelopment in occupational setting [START_REF] Julvez | Neurodevelopmental toxicity risks due to occupational exposure to industrial chemicals during pregnancy[END_REF][START_REF] Till | Prenatal exposure to organic solvents and child neurobehavioral performance[END_REF][START_REF] Laslo-Baker | Child neurodevelopmental outcome and maternal occupational exposure to solvents[END_REF][START_REF] Till | Effects of maternal occupational exposure to organic solvents on offspring visual functioning: a prospective controlled study[END_REF]. Some previous studies reported cognitive and behavioral deficits, including hyperactivity, attention deficits, lower processing speed and memory scores, reduced dexterity and visualmotor coordination) [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF][START_REF] Till | Prenatal exposure to organic solvents and child neurobehavioral performance[END_REF][START_REF] Till | Vision abnormalities in young children exposed prenatally to organic solvents[END_REF][START_REF] Nelson | Behavioral teratology of ethylene glycol monomethyl and monoethyl ethers[END_REF][START_REF] Nelson | Reproductive toxicity of the industrial solvent 2-ethoxyethanol in rats and interactive effects of ethanol[END_REF][START_REF] Pelé | Occupational solvent exposure during pregnancy and child behaviour at age 2[END_REF]. Moreover, the organic solvents may induce complex cerebral changes, resulting in the neurobehavioral dysfunction that are poorly understood. Advanced neuroimaging can provide increased sensitivity to measure such deficits and identify cerebral connections that are affected by these neurotoxicants.

Diffusion-weighted magnetic resonance imaging is a noninvasive measuring the extent of water diffusion. Diffusion-weighted imaging (DWI) can quantitatively assess the microstructural characteristics of white matter (WM) tracts [START_REF] Jones | White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI[END_REF][START_REF] Johansen-Berg | Diffusion MRI: from quantitative measurement to in vivo neuroanatomy[END_REF]. Specifically, diffusion MRI tractography methods have been developed to map out major WM pathways, allowing mapping of the brain's structural connectivity in vivo [START_REF] Mori | Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging[END_REF]. Graph theoretical analysis provides a powerful way of quantifying neural pathways and the structure of the connectomes [START_REF] Bullmore | Complex brain networks: graph theoretical analysis of structural and functional systems[END_REF]. This approach consists in modeling the brain as a complex network where nodes are associated with regions of interest and an edge strength represents the degree of connectivity between a pair of regions. Network-based algorithms provide parameters that define the global organization of the brain and its alterations within the network. The disruption of brain connectivity was shown to play a central role in the pathophysiology of several neurological and psychiatric illnesses, such as the cortico-striatothalamo-cortical network, reward circuits and limbic system [START_REF] Sporns | Structure and function of complex brain networks[END_REF].

In this paper, we investigated the specific effects of prenatal exposure to some low-level glycol ethers, called alkoxycarboxylic acids, on brain development in children aged between 10 and 12 years old. Based on previous studies suggesting cognitive disabilities in attention, inhibition and working memory networks, we proposed a structural connectivity analysis using graph theory in regions involved in these functions. Identifying the neural correlates underlying the exposure of each glycol ethers will help identify the microstructural modifications in exposed children.

MATERIAL 2.1. Population

Participants were recruited from the PELAGIE prospective cohort study of mothers and their newborn infants who were born between 2002 and 2006 [START_REF] Garlantézec | Maternal occupational exposure to solvents and congenital malformations: a prospective study in the general population[END_REF]. This cohort included 3421 women at the beginning of pregnancy recruited in general population. The children were followed during their development. Environmental as well as health condition data were collected. For the MRI project, a sub-cohort was randomly selected and children had to be born at term (delivery after 35 weeks of amenorrhea) and to present no major condition at birth (neonatal hospitalization, hypoglycemia, 5 minute-Apgar score <7), no maternal tobacco or alcohol consumption during pregnancy, no exposure to medical treatment during childhood which could affect their neurodevelopment (methylphenidate, psychotropic or antiepileptic drugs, etc.). Finally, 100 children and parents agreed to participate in a new study 10 years later. The appropriate ethics committees approved the study (Committee for the protection of persons-n°2013-A01420-45, French Consulting Committee for the Treatment of Information in Medical Research, n°09.485, and the French National Commission for the Confidentiality of Computerized Data, n°909347), and written informed consents were obtained from all subjects and parents.

Data

All children underwent MR imaging using a 3T MR Scanner (Magnetom Verio, VB17, Siemens, Erlangen, Germany) using a 32-channel receiver head coil. The 3D T1-weighted images were acquired covering the whole brain (160 sagittal slices) with TR = 1.9s, TE = 2.26 ms, flip angle= 9°, in-plane resolution = 256 × 256, FOV = 256 mm ×256 mm and thickness =1 mm). The DWI data were gathered on 60 slices using an interleaved slice acquisition order, slice thickness of 2 mm, no gap, in-plane resolution = 2 mm × 2 mm and in a 256 mm × 256 mm field of view, TR/TE = 11 000/99 ms, flip angle was 90°, pixel bandwidth =1698 Hz/px, using 30 directions and a b-value of 1000 s/mm 2 .

At inclusion, 73 women had returned a urine sample (first morning void) in a 10 mL test tube (95 × 16 mm polypropylene, with wing plug). Six alkoxycarboxylic acids (glycol ether metabolites) of the most used glycol ethers in France at the time of inclusion were analyzed: methoxyacetic acid (MAA), ethoxyacetic acid (EAA), ethoxyethoxyacetic acid (EEAA), 2-butoxyacetic acid (BAA), phenoxyacetic acid (PhAA) and 2methoxypropionic acid (2-MPA). Procedure details of chemical analyzes are described elsewhere [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF]. The children had prenatal exposures to some low-level glycol ethers [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF] and nevertheless, were categorized into 3 groups based on tertiles: low, moderate or high-level groups.

Image processing

Preprocessing of diffusion images was mainly performed using the open source medical image processing toolbox Anima (https://github.com/Inria-Visages/Anima-Public/wiki). Diffusion images were corrected for eddy current-induced image distortion using Block-Matching Distortion Correction method ensuring an opposite symmetric transformation [START_REF] Hedouin | Block-Matching Distortion Correction of Echo-Planar Images With Opposite Phase Encoding Directions[END_REF]. Then, rigid realignment was then performed to compensate for subject motion and ensure voxel-to-voxel correspondence across gradients. Then, denoising step using blockwise non-local means filtering was applied [START_REF] Coupé | An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images[END_REF]. Skull stripping was performed using an atlas-registration-based method. Whole brain WM tractography was performed using fiber assignment by continuous tracking (FACT) method [START_REF] Mori | Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging[END_REF]. Then, the individual T1-w images were coregistered to the b = 0 images in the DWI space [START_REF] Commowick | Block-matching strategies for rigid registration of multimodal medical images[END_REF]. The T1 weighted images from the included subjects were preprocessed using FreeSurfer [START_REF] Dale | Cortical surface-based analysis: I. Segmentation and surface reconstruction[END_REF] for cortical and subcortical gray matter parcellation. Our analysis was restricted to regions including in the motor inhibition, attention and working memory networks (as displayed in Figure 1.A.), such as dorsolateral prefrontal cortex and intraparietal sulcus, anterior cingulate, supplementary motor area, inferior and frontal gyrus, frontal eye fields, ventral frontal cortex and temporoparietal junction. These regions were estimated using the Freesurfer segmentation.

METHODS

Network construction

To construct connectivity matrices, we used the restricted segmentation to define the graph nodes (18 regions). For each subject group, we constructed a corresponding 18 × 18 brain connectivity matrix with each element (i,j) depicting the number of fibers that passes through regions i and j (as displayed in Figure 1.B.), normalized by the mean volume of the two regions. . The group-averaged matrices were thresholded to include only connections found in at least 75% of subjects, in order to suppress false positive fibers arising from tractography errors [START_REF] Maier-Hein | The challenge of mapping the human connectome based on diffusion tractography[END_REF].

Network analysis

To localize specific pairs of brain regions in which structural connectivity was modified by organic solvents, a two-sample Student t-test was performed after controlling for age and gender between low-and high-level groups for every solvent. A primary threshold (p < 0.01) was first applied to the t-statistic to define a set of connections. To estimate the significance for each of them, a nonparametric permutation approach (10,000 permutations) was applied. Data was randomly reallocated into two groups (high-or low-level groups) and the t-statistic was computed independently for each connection. The corrected p-value was determined by finding the fraction of t-statistics that were at least as high as the original (non-permuted) statistic.

RESULTS

We observed statistically significant difference in connectivity between left ventral frontal cortex and superior parietal cortex (t-statistic= -2.6 and p-value=0.01) between children with high (n=23) and low (n=26) exposure to BAA. We reported decreased fiber density in regions involved in attention network for children whose mothers had highest levels of BAA. This suggested that there was a possible relationship between the attention network and BAA. Statistically significant difference was found in fiber density between the caudal middle frontal cortex and the frontal cortex (rostal midlle and superior parts) (t-value= -2.3/-2.5 and p-value=0.01/0.02) between groups of low (n=28) and high (n=22) level of EEAA exposure. These regions are involved in working memory. An association between some connections of inhibition and attention network and EEAA exposure was found. The 20 children whose mothers had high levels of EEAA exhibited higher fiber density between left anterior cingulate cortex and inferior frontal region, as well as ventral frontal and superior temporal cortices in comparison with 30 low-level children. No statistical association was found between structural connectivity and level exposure of PhAA and MAA. Concerning the MPA, we observed decreased fiber density in the high-level group compared with the low level one in different connections involved in attention such as bilateral ventral frontal cortex and temporo-parietal junction. However, the statistics did not survive permutation test.

Figure 2: Regions exhibited significant between-group differences in fiber density for BAA (A), EAA (B) and EEAA (C). The blue color represented the higher values for children whose mothers had high level of exposure to glycol ethers (p<0.05 with permutation test).

DISCUSSION

To our knowledge, this is the first structural connectivity study analyzing the specific effects of prenatal low-level exposure to different glycol ethers. This preliminary study suggests that prenatal organic solvent exposure, at levels observed with routine use and below the threshold for any signs of acute exposure, has a measureable effect on brain connectivity in a sample of children between 10 and 12 years old. Our findings exhibit a decreased fiber density in prefrontal and parietal cortices associated with higher prenatal glycol ether exposure group, suggesting defects in the brain circuitry underlying performance of attention, working memory and motor inhibition. These results are appeared to be in line with studies reported association between prenatal exposures to organic solvents in general and neurocognitive deficits [START_REF] Béranger | Prenatal exposure to glycol ethers and neurocognitive abilities in 6-year-old children: the PELAGIE cohort study[END_REF][START_REF] Till | Prenatal exposure to organic solvents and child neurobehavioral performance[END_REF][START_REF] Till | Vision abnormalities in young children exposed prenatally to organic solvents[END_REF][START_REF] Nelson | Behavioral teratology of ethylene glycol monomethyl and monoethyl ethers[END_REF][START_REF] Nelson | Reproductive toxicity of the industrial solvent 2-ethoxyethanol in rats and interactive effects of ethanol[END_REF][START_REF] Pelé | Occupational solvent exposure during pregnancy and child behaviour at age 2[END_REF]. We also observed the same affected regions than the ones found for adults chronically highly exposed to solvents [START_REF] Tang | Occupational solvent exposure and brain function: an fMRI study[END_REF]. Moreover, in this study, children whose mothers had high levels of EEAA exhibited higher fiber density between two pairs of regions. This elevated structural connectivity could provide a compensatory mechanism favoring cognitive performance.

CONCLUSION

In this paper, for the first time, we were able to investigate the specific effects of prenatal low-level exposure to different glycol ethers on brain development using a structural connectivity analysis. Our results suggest that there was a possible relationship between the attention, working memory and inhibition networks and specific glycol ethers, such as BAA, EAA and EEAA. Given that this study presents limits in term of exposure measure and other confounder factors might be explored, these results need to be confirmed by other studies on potential neurotoxicity of glycol ethers. Nevertheless, our observations provide insights for future studies and suggest the interest of this kind of investigation.

Figure 1 :

 1 Figure 1: (A) Graphical representation of the nodes and (B) the mean connectivity matrix of the participants.


Daniel S Müller

Yann Raoul

Jérôme Le Nôtre

Olivier Baslé

Marc Mauduit

In Situ Generation of Ru-Based Metathesis Catalyst. A Systematic Study

Keywords: Olefin metathesis, Ruthenium, Arene complexes, in situ, NHC ligand

ABSTRACT: A practical and cost-effective protocol for the in situ generation of Ru-based metathesis catalysts was developed. Assembly of commercially available and inexpensive reagents [Ru(p-cymene)Cl 2 ] 2 , SIPr.HCl and n-BuLi led to the formation of 18 electron arene-ruthenium complexes that, in the presence of additives such as alkynes, cyclopropenes and diazoesters, generated highly selective and efficient catalytic systems applicable to a variety of olefin metathesis transformations. Notably, we were able to achieve a productive TON of 4500 for the self-metathesis of methyl oleate, a reaction which could be easily upscaled to 2 kg.

Since its discovery in the mid 1950's, the metathesis reaction gained significant importance for organic syntheses and polymer chemistry. [START_REF]Selected comprehensive books on olefin metathesis: (a) Handbook of Metathesis[END_REF] In its early days, the metathesis reaction relied on ill-defined in situ generated catalysts. Only upon the emergence of well-defined air stable Ru-complexes, such as the Grubbs 1 st generation Ru-1a, and the more performant Grubbs 2 nd generation Ru-1b containing an N-heterocyclic carbene (NHC) ligand, olefin metathesis started to significantly impact organic synthesis. [START_REF] Schwab | The Influence of the Alkylidene Moiety on Metathesis Activity. Synthesis and Applications of RuCl 2 (=CHR'(PR 3 ) 2[END_REF] Since then the field has grown steadily, resulting in numerous applications for both academia and industry. [START_REF] Higman | Olefin Metathesis at the Dawn of Implementation in Pharmaceutical and Specialty-Chemicals Manufacturing[END_REF] An early mechanistic study from Grubbs demonstrated that Ru-1a,b are in fact precatalysts which, only after dissociation of the PCy 3 ligand, provide the corresponding catalytically active 14-electron benzylideneruthenium species (Figure 1-A). 4 Obviously the dissociated ligand (e.g. PCy 3 ) is no longer needed in the catalytic cycle and has been shown to even be involved in catalyst decomposition. [START_REF]For recent investigations concerning catalyst degradation[END_REF] In the light of this, several research groups were interested to develop the in situ formation of metathesis active species from alkylidene-free Ru-precatalysts. In that respect, the 18-electron phosphine-based p-cymene-ruthenium complex Ru-2, 6 and its NHC ligated congeners Ru-3, 7 Ru-4 [START_REF] Jafarpour | p-cymene)RuLCl 2 (L = 1,3-Bis(2,4,6-trimethylphenyl)imidazol-2ylidene and 1,3-Bis(2,6-diisopropylphenyl)imidazol-2-ylidene) and Related Complexes as Ring Closing Metathesis Catalysts[END_REF] and Ru-5 [START_REF] Engel | Loss and Reformation of Ruthenium Alkylidene: Connecting Olefin Metathesis, Catalyst Deactivation, Regeneration, and Isomerization[END_REF][START_REF]E.; High-Yield Synthesis of a Long-Sought, Labile Ru-NHC Complex and Its Application to the Concise Synthesis of Second-Generation Olefin Metathesis Catalysts[END_REF] showed metathesis activity in the presence of carbene activator (Figure 1-B). [START_REF] Delaude | Retracing the Evolution of Monometallic Ruthenium-Arene Catalysts for C-C Bond Formation[END_REF] This in situ protocol was successfully illustrated in ring-opening metathesis polymerization (ROMP), 6a,12 self-metathesis 13,14d and ringclosing metathesis (RCM) reactions. 14 Of note, Thieuleux and Basset demonstrated by 1 H-NMR studies that the selfmetathesis of ethyl oleate with PCy 3 -based complex Ru-2 and (trimethylsilyl) diazomethane (TMSD) as carbene activator generated the same observable resting states as the Grubbs-1 catalyst (Ru-1). [START_REF] Ahr | Catalysts: Evidence for One Unique Active Species for Two Different Systems[END_REF] Moreover, independent studies by Fürstner 15 and Noels 12d,16 showed that light could also initiate metathesis reactions with 18-electron arene-ruthenium complexes (e.g. Ru-2). More recently, Lewis acid assisted activation of 18electron arene-ruthenium complexes containing various unsaturated NHCs was reported by Beller and coworkers as well as the influence of trace impurities upon metathesis activity. 17 Despite all these cost-effective methodologies to furnish active metathesis species from simple 18-electron Rucomplexes, few drawbacks merit to be solved to render this protocol more attractive. For instance, the most efficient Ru-5 containing the saturated NHC ancillary ligand (SIMes) is quite unstable and remains difficult to isolate. [START_REF]E.; High-Yield Synthesis of a Long-Sought, Labile Ru-NHC Complex and Its Application to the Concise Synthesis of Second-Generation Olefin Metathesis Catalysts[END_REF][START_REF] Stumpf | Ruthenium-Based Catalysts for the Ring-Opening Metathesis Polymerisation of Low-Strain Cyclic Olefins and of Functionalised Derivatives of Norbornene and Cyclooctene[END_REF] Inspired by the pioneering work of Grubbs, 14a Noels 14c,16 and Dixneuf 14b we opted for a systematic study to generate 14 electron active species by simply mixing a Ru(II) salt, an ancillary NHC precursors and a carbene activator, thus avoiding any isolation steps of unstable complexes (Figure 1). We report herein that transient alkylidene Ru-species may be readily formed by mixing inexpensive commercially available [(p-cymene)RuCl 2 ] 2 , 19 an azolium salt, a base and a carbene activator (Figure 1-this work). The choice of the base and the activator appeared to be pivotal factors in the quest for highly active catalytic species towards the targeted metathesis transformation. Furthermore, the results of this systematic approach led to the development of in situ made rutheniumcatalysts exhibiting catalytic performances that can compete with some well-defined 1 st generation catalysts (e.g. Ru-1a).

We began our study by in situ generation of ruthenium arene complex Ru-NHC from four commercially available azolium salts which were deprotonated with NaHMDS and then exposed to [(p-cymene)RuCl 2 ] (Figure 2). [START_REF]{RuCl 2 (cod)} n ] were unsuitable precursors, see ref. 14a[END_REF] There is literature precedent on the exchange of p-cymene to deuterated benzene and based on this observation, [START_REF] Engel | Loss and Reformation of Ruthenium Alkylidene: Connecting Olefin Metathesis, Catalyst Deactivation, Regeneration, and Isomerization[END_REF] it is reasonable to assume that p-cymene is rapidly replaced by toluene at 80 °C. 21 The solution of the in situ generated 18-electron complex Ru-NHC was then immediately tested for the ring-closing metathesis (RCM) of diethyl diallylmalonate 1. This reaction was carried out in the presence (Figure 2-a) and absence (Figure 2-b) of phenyl acetylene A1, [START_REF]{RuCl 2 (cod)} n ] were unsuitable precursors, see ref. 14a[END_REF] which has been previously described as a convenient and efficient activator. 14c,d In the absence of phenylacetylene, the use of SIPr.HCl salt as NHC precursor afforded the highest selectivity towards the metathesis product 2 (Figure 2-a). In fact, the noticeable activity observed using SIMes ligand precursor led mostly to the cycloisomerization product 3. Interestingly, in all examined cases a strong enhancement of the metathesis reactivity and selectivity could be observed upon the addition of 20 mol% of phenyl acetylene, 14c,d with the SIPr-based complex demonstrating the highest catalytic activity (Figure 2-b). It should be noted that a reduction of the 4:1 phenyl acetylene:ruthenium ratio significantly lowered yields and selectivities towards the metathesis product 2 (see Supporting Information; SI). Encouraged by these initial results, we decided to further investigate the influence of the base on the outcome of the metathesis reaction. Therefore, the catalytic activity obtained with 3 mol% of SIPr-based complex generated using NaHMDS was compared in terms of efficiency to catalytic systems generated from the use of other bases such as ZnEt 2 , KHMDS, n-BuLi and KOtBu (Figure 3). The catalytic systems generated from the various bases evidenced tremendous metathesis activity differences after 15 min of reaction. Whereas Et 2 Zn gave a very modest 7% yield of the desired RCM-product 2, NaHMDS and KOtBu gave significantly improved results (37% and 63% yield). The best performances were obtained with KHMDS and n-BuLi (~90 % GC-yield), which compare favorably to the previous procedure described by Grubbs requiring prolonged reaction times and higher catalyst loading for similar results (5 mol%, 10 h). 14a With the objective to provide catalytic systems of broad application, we therefore decided to continue our study with n-BuLi, which has the advantage of only producing butane and LiCl side products with low potential for interfering with the metathesis catalytic cycle. Influence of the base on the catalytic efficiency after 15 min in the RCM of diethyl diallylmalonate 1 using 3 mol% of in situ generated Ru-6. In all cases, the 2:3 ratio was >98:2.

Me

Next, we evaluated and compared the catalytic activity resulting from the use of nine different activators; 3 representatives of each activator type shown in Figure 4. First, the electronic properties of alkyne activators demonstrated an influence on the catalyst activity. While electron neutral or rich alkynes (A1 and A2) afforded the desired RCM product 2 in good 87 and 79% yield, modest 42% yield was obtained with the electron poor alkyne A3. Then, cyclopropenes additives, which have never been previously considered as activator for 18 electron arene-ruthenium complexes, proved beneficial to the performance of the metathesis reaction. Again, the electronic property of the carbene source is reflected in the catalytic activity: electron rich cyclopropene A4 22 generated a metathesis catalytic system, affording product 2 in high 96% yield, whereas the more electron deficient cyclopropenes A5 and A6 gave inferior results. Finally, the addition of diazocompounds such as A7 or A8 showed similar activity to produce the RCM product in 70% yield, whereas TMSD (A9) gave only sluggish reactivity. Concerning the activation of 18 electron arene-rutheniumcomplex Ru-6 with alkyne, cyclopropene and diazo activators we propose the mechanistic scenarios described in Scheme 1. Based on the work of Werner [START_REF] Grünwald | Five-Coordinate 16-Electron Carbene-and Vinylideneruthenium(II) Complexes Prepared from [RuCl 2 (C 8 H 12 )] n or from the New Dihydridoruthenium (IV) Compound [RuH 2 Cl 2 (P i Pr 3 ) 2 ][END_REF] and Ozawa 24 on vinylideneruthenium complexes it was speculated in the past that the addition of alkynes to 18 electron Ru-complexes would lead to vinylidene species as the active catalyst. 14 However, recent reports by Delaude on homobimetallic ruthenium complexes suggest that the initially generated vinylidene species C undergoes ene-yne metathesis with excess alkyne to produce after cycloaddition/cycloreversion benyzlidene complex E which is very likely responsible for the catalytic activity (Scheme 1-a). 25 This hypothesis is further supported by our experimental findings that an alkyne:Ru ratio inferior to 4:1 resulted in a strong drop of activity and selectivity. [START_REF]{RuCl 2 (cod)} n ] were unsuitable precursors, see ref. 14a[END_REF] For the reaction with cyclopropenes, we propose the following mechanism (Scheme 1-b). First, thermal decoordination 6b of toluene gives the coordinately unsaturated, highly reactive 12 electron ruthenium complex B which rapidly reacts with cyclopropene A4 to give the more stable -complex F. In fact a recent report by Occhipinti and Jensen described species B to be responsible for common catalyst degradation by intramolecular C-H activation and hydridemechanism isomerization. [START_REF] Engel | Loss and Reformation of Ruthenium Alkylidene: Connecting Olefin Metathesis, Catalyst Deactivation, Regeneration, and Isomerization[END_REF] Hydride ruthenium species were evoked by Beller as the responsible species for producing cycloisomerization products (e.g. 3; Figure 2). 17a An alternative isomerization pathway was proposed by Dixneuf who reported that B can promote cycloisomerization of dienes via formation of a bis--complex followed by oxidative addition, -elimination and reductive elimination. 14b This is very likely the reason why in the absence of activator the cycloisomerized product 3 was formed as the major species (Figure 2). In analogy to the corresponding tungsten complexes we then propose the subsequent formation of metallacyclopropane G which then rearranges to give the active vinyl alkylidene complex H. Alternatively, the -complex F could also react to H without formation of the metallacyclopropane intermediate. [START_REF] Nguyen | Ring-Opening Metathesis Polymerization (ROMP) of Norbornene by a Group VIII Carbene Complex in Protic Media[END_REF] Due to the known lack of stability of complex H we can expect that there will be a partial loss of material due to decomposition. 4d Therefore the in situ generated 18-electron complex A needs to be added to the activator and the substrate at the same time.

In this case the transiently generated active species H will immediately enter the catalytic cycle thus diminishing inadvertent decomposition. [START_REF]Noels demonstrated previously that it is important to add the ruthenium-arene complex to the activator and the substrate[END_REF] According to reactions between Ru-complexes and diazocompounds described in the literature, [START_REF]E.; High-Yield Synthesis of a Long-Sought, Labile Ru-NHC Complex and Its Application to the Concise Synthesis of Second-Generation Olefin Metathesis Catalysts[END_REF]29 we propose the formation of I from B and A7 under concomitant nitrogen evolution (Scheme 1-c). Indeed, gas evolution is observed even at room temperature upon addition of A7 to Ru-6.

With the optimized conditions in hand for the in situ generation of the complex Ru-6 that use n-BuLi as the base to deprotonate the SIPr ligand precursor, we investigated the substrate scope (Table 1). In order to minimize the risk of potential mismatch between substrates and activators, we decided to evaluate several activators (or no activator) for each of the metathesis reactions. RCM reactions with diallyl-Ntosylamine 4 was carried out at 80 °C and 22 °C (entries 1-8). At 80 °C complete conversion was observed with only 2 mol % of Ru-6 in combination with activator A1 (entry 2). In contrast, carrying out the same reactions at 22 °C (entries 5-8) gave similar results only with cyclopropene A4 (entry 7). This indicates that the rate determining step in the in situ formation of active 14-electron ruthenium complexes is very likely not the thermal dissociation of the toluene substituent (A → B; Scheme 1) but rather the formation of E (Scheme 1-a) in the case of alkynes. Another explanation for the sluggish reactivity with A1 and A7 at 22 °C might be that these catalytic systems require thermal activation. [START_REF] Grela | that sterically encumbered indenylidene catalysts showed much higher catalytic activity at 70 °C compared to[END_REF] Trisubstituted olefin 6 reacted cleanly in the presence of cyclopropene A4 (entry 11). Surprisingly, in the absence of activator very high RCM selectivity was observed (entry 9). This illustrates the unpredictable behavior of Ru-6 in the absence of activator, which often results in mixtures of metathesis, cycloisomerization and isomerization products (e.g. entries 13, 17 and 21) but in some cases, can also afford relatively clean reactions (entries 9 and 33). Interestingly, 6-membered RCM product 9 was obtained in high yields independent on the source of activator (entries 14-16). RCM reactions with substrate 10 were carried out either under standard conditions with non-degassed toluene (entries 17-20) or using degassed toluene (entries 21-24). In general yields and conversions were similar in the two cases. However, we found the reaction with activator A7 to be more selective towards the metathesis product 11 with degassed toluene (entries 20 and 24). For the synthesis of macrocycle 13 we noticed that the use of degassed toluene gave better reproducibility compared to standard conditions. The yields were somewhat lower compared to 7-membered cycle 11 (entries 25-28), very likely due to the formation of oligomeric side products. [START_REF] Müller | Stereoretentive Olefin Metathesis Made Easy: In Situ Generation of Highly Selective Ruthenium Catalysts from Commercial Starting Materials[END_REF] Surprisingly, activators A1 and A7 performed significantly better than A4 (entries 26-28). Cross-metathesis reactions between 14 and 15 were very sluggish and low yielding (entries 29-32). We noticed that upon addition of Ru-6 to a mixture of 14 and 15 a black slimy residue appeared within seconds. The observed degradation might be similar to the corresponding PCy 3 ligated complex which was reported to decompose in the presence of allylic alcohols. 32

AX

a Reactions carried out in argon-flushed vials with dry solvents (MBraun ® solvent system). Conversions and yields were determined by GC-analysis with internal standards (see SI). b Significant amounts of side products from cycloisomerization and isomerization processes were observed (see SI). c Reactions carried out at room temperature. d Reactions carried out in the glove-box with degassed solvents. e Low yield due to oligomeric side products. f Ru-6 was synthesized in toluene and then added to a solution of 14 and 15 in THF. Reactions in toluene afforded even lower yields. g Apart from the desired products (16 or 19) we observed products from isomerization and self-metathesis of the terminal alkene substrates (14 or 17).

This assumption gains further credence when compared to the reactions with diacetate 18 which afforded CM product 19 in good yields with all activators (entries 33-36). Having tested several RCM and cross-metathesis reactions with substrates containing terminal olefins, we then decided to focus our attention on the self-metathesis of methyl oleate (i.e. methyl (Z)-9-octadecenoate) (Z)-20 (99% purity) which is an important chemical feedstock from biomass, leading to valuable hydrocarbon 21 and mono-unsaturated diester 22 (Table 2). [START_REF] Allard | Bleaching Earths as Powerful Additives for Ru-Catalyzed Self-Metathesis of Non-Refined Methyl Oleate at Pilot Scale[END_REF] Surprisingly, activators like phenyl acetylene A1 and cyclopropene A4, which were among the best activators for RCM or CM reactions with terminal alkenes, gave poor or no conversion in the self-metathesis of (Z)-20 (entries 3 and 6). In contrast, when the reaction was carried out in the absence of activator the self-metathesis still proceeded, however producing many isomerization side-products (entry 1). The best productivity was found at low catalyst loading in the presence of diazocompounds A7 and A8 (entries 9-14). The reasons for the dramatic decrease of activity with alkyne and cyclopropene activators are still unclear. We postulate that the intermediate E generated from phenyl acetylene (Scheme 1a) is too sterically encumbered to efficiently react with the internal olefin of (Z)-20. In contrast, steric arguments cannot be evoked to explain the lack of efficiency with cyclopropene A4. In this case, the sterically more demanding cyclopropene A5 shows in fact better efficiency (entries 6-7). However, an electronic argument might be considered: Internal alkenes are more electron rich compared to terminal alkenes. Therefore, we postulate that electron poor cyclopropenes A5 and A6 lead to a better electronic match for in situ generated ruthenium catalyst with (Z)-20. On the other hand, we observed that, at high catalyst loading, the in situ generated ruthenium catalyst produces significant amounts of isomerization side-product (entries 9 and 13; see SI). Fortunately, lowering the catalyst loading to less than 500 ppm favors the metathesis reaction over undesired isomerization (entries 10-12 and 14). When working with degassed solvents in a glove box, we even achieved 45% productive conversion (50% being the

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A c c e p t e d M a n u s c r i p t maximum) with only 100 ppm of in situ generated Ru-6 and 400 ppm of activator A7 (entry 12). It is noteworthy that this is currently the best effective turn over number (TON = 4500) achieved with in situ generated ruthenium catalysts. [START_REF] Ahr | Catalysts: Evidence for One Unique Active Species for Two Different Systems[END_REF] This TON is even higher compared to effective TON previously achieved with the Grubbs-1 catalyst Ru-1 (TON = 2500). [START_REF] Dinger | High Turnover Numbers with Ruthenium-Based Metathesis Catalysts[END_REF] To demonstrate the robustness of in situ generated catalyst Ru-6, we tested the optimized catalytic system towards a non-refined methyl oleate Z-20 (technical grade, 85% purity) derived from very high oleic sunflower oils (VHOSO) on a 2-kg scale (Scheme 2). We were delighted that with only 400 ppm of catalyst full equilibrium of 20, 21 and 22 was achieved within only 1 hour at 80 °C (See SI for a detailed description of the experiments including pictures). Of note, due to the low cost of [(p-cymene)RuCl 2 ] 2 , n-BuLi, SIPr.HCl and ethyl diazoacetate A7, this catalytic system showing a TON of 1250 appeared quite competitive to the most efficient well-defined Ru-catalysts. In conclusion, we have reported a systematic study concerning the in situ formation of Ru-alkylidene catalytic species for olefin metathesis. By combining commercially available and inexpensive reagents [Ru(p-cymene)Cl 2 ] 2 , SIPr.HCl and n-BuLi in toluene, the resulting 18 electron arene-ruthenium complex promoted, in the presence of activators such as alkynes, cyclopropenes and diazoesters, highly selective and efficient catalytic systems toward a variety of olefin metathesis transformations. Furthermore, we introduced for the first time cyclopropenes as efficient activators for the in situ generation of Ru-metathesis catalysts. Our investigations concerning the self-metathesis of methyl oleate (MO) showed an unprecedented substrate dependence on the activators. The diazoester A7 was identified to be most efficient to convert the MO (Z)-20 (@99% purity) into highly valuable mono-unsaturated diester and hydrocarbon with a catalyst loading as low as 100 ppm (TON of 4500). Moreover, the robustness of the newly developed catalytic system was demonstrated with the 2 kg-scale transformation of a nonrefined technical grade MO (Z)-20 (85% purity) using only 400 ppm of catalyst loading (TON = 1250). This highly competitive and cost-effective catalytic process is underway in other valuable metathesis transformations.

Figure 1 .

 1 Figure 1.Previous strategies used for the formation of 14-electron Ru-active species toward olefin metathesis (A and B). The proposed synthetic route involving inexpensive commercially available reagents (this work). SIMes = N,N'-bis-mesityl-imidazolin-2-ylidene

Figure 2 .

 2 Figure 2. Ratio of RCM-product 2 (blue) and cycloisomerization product 3 (red) in the absence (a) and in the presence (b) of phenyl acetylene A1. SIPr = N,N'-bis-2,6-iPr-C 6 H 3 -imidazolin-2-ylidene.

  Figure3. Influence of the base on the catalytic efficiency after 15 min in the RCM of diethyl diallylmalonate 1 using 3 mol% of in situ generated Ru-6. In all cases, the 2:3 ratio was >98:2.

Figure 4 .

 4 Figure 4. Screening of activators for the RCM of diethyl diallylmalonate 1.

26

 26

  Scheme 1. Postulated mechanisms for the activation with alkynes, cyclopropenes and diazocompounds

a

  Scheme 2. Kg-scale self-metathesis of non-refined methyl oleate (Z)-20 (technical grade, 85% purity) catalyzed by optimized in situ catalytic system Ru-6/A7a Radia 7072 is commercialized by Oleon.b The other compounds were identified as saturated and mono-or poly-unsaturated fatty methyl esters: C16:0 (3.4 wt.%); C16:1 (0.1 wt.%); C18:0 (1.8 wt.%); C18:2 (3.1 wt.%); C18:3 (1.8 wt.%); C20:0 (0.2 wt.%) C22:0 (0.3 wt.%) and C22:1 (0.7 wt.%). c Determined by GC.

Table 1 . Reaction scope. a

 1

	M a n u s c r i p t
	A c c e p t e d

Table 2 : Screening of activators for the self-metathesis of methyl (Z)-9-octadecenoate (Z)-20 (99% purity) a

 2 Reactions performed in argon flushed vials on a 0.3 mmol scale (MO of 99% purity, Sigma Aldrich; used as received). The other products observed are unidentified isomerization products; see SI. b Determined by GC. c Carried out on a 8.0 mmol scale. d Reactions were carried out in the glove box (See SI for details).

					used in situ
					Me
								6
	6	O	OMe	Ru Ru-6 (y mol %) Cl Cl SIPr		6 (E/Z)-21 +	O	+	6	O	OMe
	6 (Z)-20	toluene, 80 °C, 2 h A1-9 (4 x y mol%)	MeO	6	6		OMe	6
						O	(E/Z)-22			(E/Z)-20
	Entry		Ru-6 (y mol %)	AX	20 (%) b (Z:E ratio)	21 (%) b	22 (%) b (Z:E ratio)
	1		2		none	36 (21:79)	15		15 (25:75)
	2 c		0.1		none	93 (59:41)	3			3 (32:68)
	3		2		A1	100 (>99:1)	0			0
	4		2		A2	100 (>99:1)	0			0
	5		2		A3	100 (>99:1)	0			0
	6		2		A4	92 (82:18)	4		4 (30:70)
	7		2		A5	51 (24:76)	20		21 (22:78)
	8		2		A6	68 (35:65)	16		16 (24:76)
	9		2		A7	38 (21:79)	18		18 (25:75)
	10 c		0.05		A7	51 (21:79)	24		24 (23:77)
	11 d		0.02		A7	51 (21:79)	24		25 (22:78)
	12 d		0.01		A7	55 (30:70)	22		23 (24:76)
	13		2		A8	15 (13:87)	19		16 (19:81)
	14 c		0.05		A8	50 (21:79)	24		24 (24:76)
	15		2		A9	72 (32:68)	14		14 (27:73)

a

  [START_REF] Allard | Bleaching Earths as Powerful Additives for Ru-Catalyzed Self-Metathesis of Non-Refined Methyl Oleate at Pilot Scale[END_REF]

				Me
							6
	6	O	OMe	Ru Ru-6 (0.04 mol %) Cl SIPr Cl			6 + (E/Z)-21	O
	6 (Z)-20 from non-refined VHOSO (Radia 7072) a (85% purity) b	toluene, 80 °C, 1 h	MeO	O	6 (E/Z)-22	6	OMe
				A7 (0.16 mol%)

ACKNOWLEDGMENT

This work was supported by the FASO (grant to DSM; Z-SELECT) and the Région Bretagne (SAD 2016 N° 9639 -RZSELECT; grant to OB and DSM). OB and MM acknowledge the Ecole Nationale Supérieure de Chimie de Rennes (ENSCR) and the Centre National de la Recherche Scientifique (CNRS) for financial support. Umicore AG & Co is acknowledged for a generous gift of [(p-cymene)RuCl 2 ] complex.

ASSOCIATED CONTENT

Supporting Information. Optimization reactions, experimental procedures and characterization data ( 1 H NMR, [START_REF] Ahr | Catalysts: Evidence for One Unique Active Species for Two Different Systems[END_REF] C NMR, GCtraces). This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION

Corresponding Author * E-mail: marc.mauduit@ensc-rennes.fr

ORCID


Julie Rivet

Guillaume Tochon

Serge Meimon

Michel Paques

Thierry Géraud

Michaël Atlan

Deep neural networks for aberration compensation in digital holographic imaging of the retina

DEEP NEURAL NETWORKS FOR ABERRATIONS COMPENSATION IN DIGITAL HOLOGRAPHIC IMAGING OF THE RETINA

Julie Rivet 1,2 Guillaume Tochon 1 Serge Meimon 3 Michel Paques 4 Thierry Géraud 1 Michael Atlan

ABSTRACT

In computational imaging by digital holography, lateral resolution of retinal images is limited to about 20 microns by the aberrations of the eye. To overcome this limitation, the aberrations have to be canceled. Digital aberration compensation can be performed by post-processing of full-field digital holograms. Aberration compensation was demonstrated from wavefront measurement by reconstruction of digital holograms in subapertures [START_REF] Kumar | Subaperture correlation based digital adaptive optics for full field optical coherence tomography[END_REF], and by measurement of a guide star hologram [START_REF] Liu | Phase aberration correction by correlation in digital holographic adaptive optics[END_REF]. Yet, these wavefront measurement methods have limited accuracy in practice. For holographic tomography of the human retina, image reconstruction was demonstrated by iterative digital aberration compensation, by minimization of the local entropy of speckle-averaged tomographic volumes [START_REF] Hillmann | Aberration-free volumetric high-speed imaging of in vivo retina[END_REF]. However image-based aberration compensation is time-consuming, preventing real-time image rendering. We are investigating a new digital aberration compensation scheme with a deep neural network to circumvent the limitations of these aberrations correction methods. To train the network, 28.000 anonymized images of eye fundus from patients of the 15-20 hospital in Paris have been collected, and synthetic interferograms have been reconstructed digitally by simulating the propagation of eye fundus images recorded with standard cameras. With a U-Net architecture [START_REF] Ronneberger | U-net: Convolutional networks for biomedical image segmentation[END_REF], we demonstrate defocus correction of these complex-valued synthetic interferograms. Other aberration orders will be corrected with the same method, to improve lateral resolution up to the diffraction limit in digital holographic imaging of the retina.The measurement of medical images can be hindered by blur and distortions caused by the physiological motion. Specially for retinal imaging, images are greatly affected by sharp movements of the eye.

Stabilization methods have been developed and applied to state-of-the-art retinal imaging modalities; here we intend to adapt them for coherent light detection schemes. In this paper, we demonstrate experimentally cross-correlation-based lateral and axial motion compensation in laser Doppler imaging and optical coherence tomography by digital holography. Our methods improve lateral and axial image resolution in those innovative instruments and allow a better visualization during motion.

2 1

 2 EPITA Research and Development Laboratory (LRDE) 2 ESPCI Paris, PSL Research University, Sorbonne Université, CNRS, Institut Langevin 3 ONERA -the French Aerospace Lab 4 Institut de la Vision, CIC 1423, INSERM UMR-S 968, CNRS, Sorbonne Université