Djilali Benyoucef

Bachir Mohammed Yousfi

M Yousfiu P

B Belmadani

RF discharge characteristics from particle model based on two optimized Monte Carlo methods for collision treatment

come

RF discharge characteristics from particle model based on two optimized Monte Carlo methods for collision treatment

Introduction

Low pressure RF electrical discharges are used as many plasma devices for e.g. thin film synthesis using a physical vapour deposition from ceramic sputtering for applications to gas sensor (see e.g. ref 1). The optimization of such RF plasma devices needs various experimental investigations coupled with discharge modelling.

Modelling of electrical, physical and chemical characteristics of RF low pressure discharge (due to the high non equilibrium processes inherent to these low pressure plasmas) needs the use of particle models rather than the fluid models. The latter are better adapted in the case of pressure plasma reactors. However, particle models based on Monte Carlo method for the collision treatment have to be optimized in order to avoid the drawback of the huge time consuming. Indeed, such optimizations are required in order to investigate, under reasonable calculation times, the RF discharge properties as a function of the different discharge operating parameters.

The aim of the present paper is to analyse, in the framework of PIC/MC model, two methods of collision treatments. The first one is based on an optimized calculation of the collision free path which is energy independent and the second one is based on the free time of flight calculation using the classical null collision technique. To do that, argon at 50 mtorr up to 100mTorr is chosen as a gas test (for RF frequency 13.56 MHz and voltage 200 V) in the case of an asymmetric reactor in a 2D cylindrical geometry.

Methods of calculation

The electrical behaviour of our low pressure RF discharge (i.e. space charge electric field and plasma potential, distribution function of charged particle, their densities, fluxes, ionization rates, etc.) are obtained from a PIC/ MC code in which collisions are treated from Monte Carlo technique and the space charge electric field is calculated from Poisson equation solution. As usual, electrons and ions are not considered individually but as pseudo-particles. The size of each pseudo particle corresponds to a large number of real particle because of the charged particles multiplication by ionization processes in the sheath region of the discharge (see e.g. ref 2 for more details on particle model description and pseudo particle size choice). In the following we use the term "particle" to designate a pseudo-particle. The treatment of the collision by using the stochastic Monte Carlo method can be done either from free path calculations as e.g. Itoh and Musa [START_REF] Itoh | [END_REF] or from free time of flight calculations as e.g Skulerud [3].

Collision treatment from free path:

Every charged particle having a kinetic energy ε can undergo N kinds of collisions i.e. elastic one, excitation and ionisation in the case of electrons and elastic one and charge transfer in the case of ions. So, the total cross section is given by:

∑ = = N i i T 1 ) ( ) ( ε σ ε σ σ i (ε)
is the cross section for the collision kind i.

The free path between two collisions depends on the background gas density n(s) at the point s and the energy of incident particle as following:

Topic number: B5 ) ( ). ( 1 ) ( ε σ ε λ T vol s n = If P(s)
is the probability of the particle moving without collision; the collision probability at point s "1-P(s) " can be written as.:

) ) ( ) ( exp( 1 ) ( 1 0 ∫ - - = - s T ds s n s P ε σ
s is the distance covered after the last collision. To determine the distance where the particle undergoes a collision, it is necessary to calculate the collision cross section during the motion of the particle because the energy continually of the particle changes due to the electric field action. Then, we have to integrate the previous relation along the trajectory of the particle; this obviously takes a non negligible computing time because we no analytical solution. To save calculation time, a minimum and constant free path λ min is considered. In the case of a uniform background gas density, λ min is analytically deduced from previous equation and therefore can be directly obtained from:

{ } ) ( max . 1 min ε σ λ T n =
As we considered the maximum value of total collision cross section to calculate λ min , we necessarily introduce the classical notion of fictitious (or null) collision because the real cross section is energy dependent.

To obtain the distance S vol between two successive collisions (i.e. the free path), we assume that:

1-P(S)=R

where R is a random number uniformly distributed between 0 and 1. Therefore, S vol can be calculated from:

) 1 ln( min R S vol - - = λ
Under these conditions, after every free path, our particle can undergo either a real or fictitious collision. The inverse of the minimum free path λ min can be written as a function of the different kinds of collisions: Once the collision type is known, it is possible to calculate the velocity vector of the particle from classical mechanics formalism.

( ) ⎪ ⎪ ⎪ ⎪ ⎩ ⎪ ⎪ ⎪ ⎪ ⎨ ⎧ + + + + = + + + + = + + + + =
( ) ( ) { } ε σ ε σ λ λ T i i i P max min = = } { } { } { } { ⎪ ⎪ ⎪ ⎪ ⎪ ⎩ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ ⎧ 〈 〈 〈 〈 〈 ∑ collision null R type R type R T N i i

Collision treatment from free time of flight:

As already emphasized, the collision kind can be obtained not only from the free path but also from free time of flight. This is largely detailed elsewhere (see e.g. Yousfi et al [5]). To summarise, we have to define not a total collision cross section but a total constant collision frequency ν max =max{n.υ(ε).Σσi(ε)}. This necessarily includes real and null collisions. In this case, the free flight time is given by:

t vol = ln(1-R)/ν max ,
where R is a random number uniformly distributed between 0 and 1.

Result and discussion

In the following calculations are done in the case of RF discharge in Ar background gas at 50 mtorr up to 100 mTorr for a RF frequency of 13.56 MHz and a RF voltage 200 V in the case of an asymmetric reactor in a 2D cylindrical geometry. Poisson's equation is solved in the same geometry by taking the average density of the particle charged for the points which have the same distance (r) to the axis of revolution symmetry. In order to ensure that RF discharge reactor is operating in a capacitive mode, its external electric circuit must include a blocking capacitor C B , having negligible impedance at the driven frequency, in order to compensate for charge accumulation due to the asymmetric configuration (see e.g. Refs 4,6). Figure 1 shows the schematic of the simulation domain and its boundaries conditions. Electron and Ar+ ion collision cross sections are similar to those considered in the literature (see e.g. ref 7).

Comparison between free path and free time of flight technique

In the case of our RF discharge at 100 mTorr for Ar gas pressure, figure 2 shows the spatial variation of electron densities obtained after a large number several RF cycles. This comparison is between our particle code using free path technique and the code using the free time of flight technique. Both results are in a very good agreement but with a computing time slightly lower in the case of the particle code using the free flight method. But, this does not mean that the free flight method is faster because in this case we used two energy intervals (not yet used in the case of the free time of flight method) which automatically reduces the number of null collision. Electron density (cm-3) free flight time free path Fig. 2. Comparison along the discharge axis between the results obtained from particle model using free flight time and free path for the collision treatment in the case of a RF voltage of 200V at 13.56Mhz and 100 mtorr of Ar pressure.

Comparison with experiment

In order to show the validity of the present particle model, calculations are done in the case of experimental conditions of Hopkins et al [8] where the electron density it measured from two different techniques: a direct measurement by using an interferometer and an indirect measurement where the electron density is estimated through the ion density with a correction factor. Figure 3 shows the comparison between the densities calculated in the centre of the discharge at 6.66 Pa and 13.33 Pa of pressure. The agreement can be considered as acceptable because the calculated results remain inside the relative measurement error (i.e. % 20 ±

).

2D RF discharge characteristics:

Figure 4 shows the results obtained in the case of an argon discharge in a cylindrical parallel plate reactor shown in Fig. 1, where D a =22 cm, D c =20 cm et d =2.54 cm, the discharge is powered by 200V RF The simulation is started by assuming a null value for the self-bias voltage V dc . In permanent mode the potential in the simulation domain remains positive, except near the driven electrode where it decreases rapidly to the value of the self-bias voltage V dc which appears just at the driven electrode Fig4(a). The electrons density and the ions density are displayed respectively in Fig4(b) and Fig4(c). As expected, these densities are quasi-equal in the plasma region. Differences start to appear beside the lateral grid due the double expansion of the radial and axial sheaths. Obviously, electrons density and ion densities become completely different in the sheath regions more particularly in the driven electrode area in the beginning of the RF cycle (i.e. T=0) due to the self-bias voltage.

Finally, the present particle model gives very similar results in the two optimized cases of collision treatment by Monte Carlo methods: the free path technique and the free time of flight one. This is a first validation test. This followed by comparisons with experimental data of literature which are satisfying because within the experimental error. Then the 2D results on electrical characteristics in the case of an asymmetric of RF discharge reactor behave as expected in the different discharge regions. In the future, the present particle code will be adapted to the case low pressure RF reactor involving both electric and magnetic field for oxide thin film synthesis from ceramic sputtering.

  the following relation of the probability Pi of the collision occurrence:

  ....... ..........

Fig. 1 .

 1 Fig.1. Schematic representation of the simulation domain and its boundaries conditions.

Fig. 3 .

 3 Fig.3. Comparison between present calculations and experimental measurements [8] at 200V for RF voltage at 13.56 MHz.

Fig. 4

 4 Fig.4 Spatial variation at the beginning of the RF cycle (T=0) for a RF voltage of 200V at 13.56 MHz and 50 mtorr of gas pressure; (a) plasma potential, (b) electron density (c) ion density.


Domingo Torres

Hervé Mathias

Hassan Rabah

Serge Weber

A new concept of a mono-dimensional SIMD/MIMD parallel architecture based in a content addressable memory

Keywords: Parallel architecture, image processing, content addressable memory, SIMD processors, MIMD processors, interconnection network

A new concept of parallel architecture for image processing is presented in this paper. Named LAPMAM (Linear array processors with Multi-mode Access Memory), this architecture, for a 512 x 512 image, has 512 processors and four memory planes each of 512² memory modules. One important characteristic of this architecture is its memories modules that allow different access modes: RAM, FIFO, normal CAM and interactive CAM. This particular memory and a linear structure of RISC processors are combined with a tree interconnection network to obtain very efficient 1-d architecture suitable for real time image processing. The processor works in SIMD mode and allows a restricted MIMD mode without requiring a great hardware complexity. A hardware simulation of an architecture prototype has been accomplished to test its performance in low and intermediate level vision tasks. The performance of the LAPMAM is compared with that of different architectures.

Introduction

The computational demands of image processing have generated a large number of research work and led to numerous architectures and algorithms [START_REF] Kumar | Parallel Architectures and Algorithms for Image Understanding[END_REF][START_REF] Downton | Parallel Architectures for Image Processing[END_REF][START_REF] Jeon | Reconfigurable Mesh Algorithm for Enhanced Median Filter[END_REF]. Sequential machines, which require an excessive amount of time, are not well suited to solve these problems. Consequently, the potential of parallelism has been highly exploited. Among the existing topologies, the most attractive in terms of processor x time complexity [START_REF] Alnuweiri | Parallel architectures and algorithms for image component labeling[END_REF] is the 1-d array processor family. The 1-d architectures are also, en general, the cheapest topologies. However, because of a lack of parallelism in the memory rows, they have a lower performance than more complex architectures (2-d architectures example). To solve this problem, we have developed systems based on CAM memories: an efficient architecture dedicated to labeling and a more general architecture called LAPCAM (Linear Array Processors with Content-Addressable Memory) [START_REF] Mozef | Design of Linear Array Processors with Content Addressable Memory for Intermediate Level Vision[END_REF]. We have redesigned the LAPCAM architecture, particularly the Multi-mode Access Memory (MAM) modules to enable the hardware implementation. The CAM mode of this memory enhances the parallelism in the memory rows of the linear arrays. In this architecture, a new concept of SIMD/restricted MIMD processors is also proposed. The processor has the SIMD structure with its typical advantages (simple implementation, high performance and no memory access conflicts), but also can work like a MIMD processor, taking a limited conditional decision with a simple control logic.

This paper describes the new linear array processor architecture based on MAM (LAPMAM), its Multi-mode Access Memory, the structure of the SIMD/restricted MIMD processing element, its interconnection network and the performance results of the hardware simulation of a prototype. A comparison between LAPMAM and others image processing architectures is finally given.

LAPMAM architecture

The LAPMAM is a linear array of RISC SIMD/restricted MIMD processors with a Multi-mode Acces Memory. The LAPMAM has four memory planes that are dependent tanks to the bidirectional heteroassositive CAM property. A controller gives the instructions word to each PE. The PE-PE and PE-MAM communications are carry out by a tree interconnection network and by a local bus (Memory bus) between the PEs and its corresponding row of memory modules.

The LAPMAM architecture for a 512 x 512 image (n=512) is shown on Figure 1. It features n processors organized in a linear array. Each of them is connected to a row of n memory modules. A special interconnection network allows every processor to reach any of the other processors and their associated memory rows. This network presents a tree structure and ensures global communication in O(log n) units of propagation time.

LAPMAM has four identical memory planes of log 512 bits denoted M A1 [i,j], M A2 [i,j], M B1 [i,j] and M B2 [i,j] (0 ? i,j ? 511). Each plane consists of 512 rows, each containing 512 memory modules. The four planes can be turned into two planes M A [i,j] and M B [i,j] of 2 log 512 bits. On Figure 1 the planes M A1 , M A2 , M B1 , M B2 are represented by the memory modules (M).

Multi-mode Access Memory

This Multi-mode Access Memory (MAM) module is basically a modified CAM. The CAM is a memory with addressing based on its content. This is an excellent solution in some applications where the RAM, with addressing based on its location, shows limited performance. The main advantage of the CAM is its capability to write/read a data to/from multiple locations in only one clock cycle or O(1) time. The concept of CAM was introduced in 1956 [START_REF] Slade | A Cryotron Catalog Memory System[END_REF]. Despite its relatively high cost, CAM has found since then enormous importance in various applications like data base management [START_REF] Yau | Associative Processor Architecture -A Survey[END_REF][START_REF] Chisvin | Content-Addressable and Associative Memory: Alternatives to the Ubiquitous RAM[END_REF] and image processing [START_REF] Shin | A Special-Purpose Content Addressable Memory Chip for Real-Time Image Processing[END_REF][START_REF] Fujino | Facial Image Tracking System Architecture Utilizing Real-Time Labeling[END_REF].

The CAM enhances the parallelism of this architecture because this memory works inherently in parallel. However, its utilization reduces the processing flexibility since the CAM can not be addressed by its position and the CAM reading is difficult. We have designed a CAM based memory with the possibility RAM and FIFO to solve the limitation of the CAM pure, it was called Multi-Mode Access Mem- The MAM modules constitute either four log n bits wide or two 2 log n bits wide memory planes. The four planes enable the architecture to work with algorithms that need to store intermediate results.

The image loading procedure is also made simpler thanks to this new possibility: an image frame may be stored in one memory plane while the previous is still under processing. The size of the memory words depends on the algorithms being run (18 bits for labeling and 9 bits for median filtering for example). The CAM and RAM operation can be carried out in a whole plane, in a row (PE-MAMs) or in several rows of a plane. The FIFO operation is only carried out in the couples PE-MAMs.

The functional diagram of a MAM module (Figure 4) consists of four log n bits registers, a little control logic made of several elementary gates, one comparator (C) and two multiplexers. The comparator makes a comparison between the content of any of the four registers and the data issued from the address bus. The writing plane is defined by the comparator result and the write control signals.

The processing element (PE)

The LAPMAM processing element was designed to exploit the Multi-mode Access Memory possibilities. The philosophy design of the PE was develop a simple RISC processor that allows exploit all the MAM possibilities trying of obtain a small element to integrate in a chip the greatest number of couples PE -row of MAM. Taking the above consideration, we propose a SIMD processor for our architecture with the possibility of take some decisions. Each PE can be activated or deactivated independently. The PE is able to compute a basic logical or arithmetic operation in O(1) time. It can communicate in O( 1) units of propagation time with its adjacent PEs or with its associated memory modules. Furthermore, it can communicate in O(log n) units of propagation time either with its non-adjacent PEs or its nonadjacent memory modules through the interconnection network.

Processor architecture

Each processor features sixteen 9-bits registers, an 18 bits arithmetical and logical unit (ALU), a 28 bits x 4 internal memory, flag registers and a small decoder. It distributes the signal controls to the different elements of PE. The processor has reduced instruction-set computer (RISC) load/store architec- When the processor is connected directly to its memory row, the access to the data contained in this line is accomplished by means of the FIFO, RAM and CAM modes. In the FIFO mode the data of the PE are transferred to the last MAM module of the row.

Using the tree interconnection network, a processor can be connected to several memory rows or even to all memory rows. This depends on the interconnection network programming. To enable the communication between PEs, each PE has a data output toward its adjacent PEs (upper PE, lower PE). The data output of each PE is taken at the point O on Figure 3. The data output of each processor can be activated or deactivated independently: the PEs have a particular address in the register 0, which is compared to the addressee sent by the general controller, thus allowing to select which PEs are active. This is quite useful when a PE needs to take control of several memory rows. To accomplish this, the remaining PEs are deactivated. The PE can work with 9 or 18 bit words, their inner registers being addressable either as a 9 or 18 bits register. This possibility used when the LAPMAM architecture process algorithms that need to execute data operation with more than 9 bits like our algorithms of labeling and area computing. The PE has also a 18 bits shift register that allows the data transfer to the video interface or vice versa.

Restricted MIMD mode

A SIMD PE is characterized by its reduced size. But, because it does not have a unit control, these types of PEs can not take internal decisions. Then, to execute different operations on different data, an architecture SIMD has to connect and disconnect the processor as many times as the number of different operations. On the other hand, the MIMD processor, that has a unit control, can take internal decision, but they are very much complex. It limits the number of PEs in an integrated circuit. We are designed a SIMD processor that can take some internal decisions, this possibility increment the flexibility of the LAPMAM architecture avoiding the connection and disconnection of PEs pour perform different instructions, reducing the computing time. This particular characteristic will be called restricted MIMD mode because the processor can only take a few decisions. For working in this way each processor stores in its internal memory a limited number of subinstructions [START_REF] Alnuweiri | Parallel architectures and algorithms for image component labeling[END_REF]. The selection of one of these subinstructions depends on the flags previous results that are stored in the flag registers, they are the input address of the sub-instruction memory. The controller has a bit that allows the output of the subinstruction memory to the instruction decoder. In the SIMD mode the instructions come directly of the instructions word, but in the restricted MIMD mode the instructions arrive from the sub-instructions memory. In this last mode each PE executes an instruction that depend of its internal flags registers. Then, the LAPMAM can execute different instructions on different data.

The interconnection network

We have design a tree interconnection network type that complements the couple PE-MAMs. This network allow performing the communications PE-PE or PE-MAMs in O(log n), but in some case it can be executed in O [START_REF] Kumar | Parallel Architectures and Algorithms for Image Understanding[END_REF], possibility that we are exploited in our algorithms. Moreover, this network has the characteristics of modularity and extensibility that allow to the network to be constructed from a small set of basic modules and to be extended to a larger size [START_REF] Siegel | A survey of interconection methods for reconfigurable parallel processing systems[END_REF]. These possibilities are very interesting for a VLSI implementation.

The interconnection network is reconfigurable by n+(3n/4)-1 switch modules denoted S g . Each switch S contains (4 log 512 + 2) three states buffers. The PE-PE and PE-MAMs connections can be carried out in regions. Some PEs can be connected to a region of 2, 4, 8 etc. elements (PEs or rows of MAMs). This connection allows certain PEs to do a regional or global communication in O(1) with a propagation delay of O(log n). But, in general, a global communication time of O(log n) is obtained with this type of network [START_REF] Almasi | Highly Parallel Computing[END_REF]. Furthermore, its special form allows all processors P j to simultaneously write/read directly to/from their current row j in only O(1) time. A tree interconnection network for architecture with eight PE is presented on Figure 4.

The network has a system protection to avoid possible conflicts between PE outputs because a program mistake may connect two PE to the same memory bus. To solve this problem, the PEs with output activated disable the network data input to their memory bus automatically. Thus, each PE controls the closest switch module of the network as it is shown on Figure 4.

Performance

In order to validate the LAPMAM architecture, we have performed a hardware simulation of a prototype of 8 PEs with 8 MAM rows. The algorithms of labeling, area and perimeter computation, histogramming and median filter were implemented on this prototype. These algorithms use the architecture properties to obtain a quasi-optimal complexity [START_REF] Jeon | Reconfigurable Mesh Algorithm for Enhanced Median Filter[END_REF]. All these algorithms have a O(n log n) complexity, except the median filter that has the optimal O(n) complexity for this type of architectures. The hardware simulation shows that the architecture can work with a 50 MHz frequency. All the algorithms were simulated at this frequency and the results, which were extended to 512 PEs architecture, are shown and compared with others architectures in Table 1.

LAPMAM computes these low and intermediatelevel image processing algorithms much faster than the video rate.

The best performance results of the DARPA II image understanding benchmark [START_REF] Weems | The DARPA Image Understanding Benchmark for Parallel Computers[END_REF] for the algorithms evaluated are compared in the first part of the Table 1. The architectures included are the Connection Machine (CM) with 64 K of PE, the Associative String Processor (ASP) that has 262,144 processors and the Image Understanding Architecture (IUA) that consists of three difference processors: low level SIMD PEs (processor-per-pixel), 4096 intermediate level SIMD/MIMD 16 bits processors, and one high level multiprocessor. For the tasks compared, our architecture is among the best ones while being the least complex. On this benchmark, only IUA has better results for labeling. However, it features for many more processors than our architecture. Otherwise, LAPMAM has the best computation times. This does not necessary mean that our architecture is much better than the others, since these architectures are very different and the technology evolution is not considered. Nevertheless, it gives a good idea of the LAPMAM's potential in low and intermediate level tasks.

In the second part of the Table 1, the LAPMAM estimated performances are compared with architectures that are more similar to LAPMAM: VIP [START_REF] Chang | A linear Array Parallel Image Processor: SliM-II[END_REF], SliM-II [START_REF] Chang | A linear Array Parallel Image Processor: SliM-II[END_REF] and IMAP VISION [START_REF] Fujita | IMAP-VISION: An SIMD Processor with High-Speed On-Chip Memory and Large Capacity External Memory[END_REF]. In this comparison, our architecture has the best results for these algorithms. Its enhanced parallelism allows the reduction of the algorithms complexities. The use of CAM and the tree structure of switches in interconnection network make the LAPMAM extremely efficient in terms of connected component analysis and median filtering tasks [START_REF] Torres | Efficient low and intermediate level vision algorithms for the LAPMAM image processing parallel architecture[END_REF]. However, because of the MAM modules, the architecture is more complex than the ones that use RAM. LAPMAM thus necessitates a full custom approach for its hardware implementation.

Conclusion

The LAPMAM architecture and its estimated performance have been presented. This is a new design of linear array processors using content addressable memory. The use of CAM modules increases the row architecture parallelism. The typical function of the CAM has been modified to obtain a more flexible memory with a multi-mode access featuring RAM, FIFO and CAM. The algorithms for labeling, area, perimeter, histogramming and 3x3 median filtering have been implemented in a LAPMAM prototype to test their performance. The Hardware simulation results demonstrate the efficacy of LAPMAM for low and intermediate level vision tasks. The use of a tree structure of switches interconnection network has also proved to be an excellent solution to decrease the data propagation time.

Globally, the architecture presents very good performance for image processing. It will be confirmed with the development of other algorithms and the LAPMAM hardware implementation.

Figure 1 Figure 2 :

 12 Figure 1: The LAPMAM architecture

Figure 3 :

 3 Figure 3: Processor architecture

Figure 4 :

 4 Figure 4: Tree structure interconnection network for LAPMAM architecture with 8 PE and 8x8 MAMs.

Table 1 :

 1 The LAPMAM estimated time results compared with others architectures (time in ms)

		DARPA II Benchmark	LAPMAM similar architectures	LAPMAM
			results
	Algorithm	for a 512x512 image	VIP	SliM-II	IMAP-VISION	50 MHz,
					1024 PEs,	512 PEs,	512 PEs, 40	512 PEs,
		CM 64 K ASP	IUA	50 MHz	40 MHz	MHz, 256x240	512x512
							image	image
	Labeling	100	22.8 0.0596	-	-	19.5*	0.614
	Median filter	15	0.72 0.5625	3.672	2.525	1.07	0.184
	Histogram	-	-	-	-	3.313	1.33	0.420
	* Worst case example


Jacques Glowinski

Jean-Antoine Girault
email: jean-antoine.girault@inserm.fr

Bernard Scatton
email: bscatton@club-internet.fr

Michel Hamon
email: michel.hamon@inserm.fr

Jacques Glowinski, « Glo » as everybody fondly called him in his lab and beyond, one of the last giants of Neuropharmacology, sadly died from the complications of Covid-19, on November 4, 2020. He was one of the early major contributors to Neuropharmacology and a founding father of this discipline in France. Many neuroscientists trained in his lab at the Collège de France, established themselves throughout the world (in Europe, United States, Mexico, Canada, Uruguay…) and are still very active in basic and clinical neuroscience research [START_REF] Glowinski | Développement d'une école de neuropharmacologie au Collège de France[END_REF].

Jacques, « Glo », was someone exceptionally charismatic, deeply human, warm, generous, and faithful in friendship, who knew how to make people around him happy. At barely 30 years old, he established a research group at the Collège de France in the small space provided by Pr. Alfred Fessard. This group, which was famously known as the NB group (for Neuropharmacologie Biochimique, i.e. Biochemical Neuropharmacology), became a few years later the so called Unit 114 of INSERM (the French Institute for Health and Medical Research), with an internationally acknowledged success over the subsequent four decades. Numerous visitors and colleagues came from France and all over the world to give seminars and for stays of various durations. All of them, including ourselves who had the fortune and privilege to work with Jacques for many years, kept the memory of a warm and friendly laboratory.

Typically, the intensely scientific day started with a meeting around tea or coffee, then, for many years, the lunch meal (dishes like at home, what a treat!) was prepared by two lovely ladies, Simone and Suzanne, and tea was served around 5 pm. These friendly moments were an opportunity to meet, to talk about science of course, but also about our lives and the world, all in a warm family-like atmosphere extremely favorable to creativity and profound dedication to research.

One year, after the summer of 1976, when financial support was low, Glo even proposed to his collaborators to make a few weeks break to repaint the lab, which was badly needed. The work was achieved cheerfully by everyone, including David L.

Nelson, a young post-doc who had just arrived from Philadelphia the day before, and research was back on the road in a snap in a renovated stimulating environment with the group energized and bonded by Glo's leadership.

As Jacques wrote in his inspiring autobiographic book, written with François Cardinali, « Le cerveau-architecte » [START_REF] Glowinski | Le Collège de France dans le XXI e siècle -Le Cerveau-Architecte[END_REF], he was born in 1936 to a family of Jewish immigrants from Poland and did not have a privileged preparatory background for graduate studies. His parents owned a fur shop with a workroom and he was a young child during Nazi occupation but, fortunately, was not captured because he was hidden with part of his family in a farm in the middle of France. After the Liberation, he grew up in a clothing business environment and worked at the end of the week as a salesperson to eke out his existence. Under the influence of his uncle Henri, a pharmacist, resistant fighter and communist, he started to become interested in studies as well as handball that he played at a high (international university) level. Jacques was seduced and so was Julie, and in the fall of 1963, he, with his wife Isabelle and their very young son, Stéphane, boarded the liner, France, heading for a 2-year visit to Bethesda. In Julie Axelrod's small lab, Jacques teamed up with Leslie Iversen and Solomon Snyder, becoming close friend with both. Together with them, Jacques revealed the full measure of his talents leading to major discoveries on brain catecholamine uptake and catabolism, and on the mechanism of action of antidepressant drugs newly introduced into the clinics. His innovative technique for intracerebroventricular microinjections in the rat allowed important studies of the activity of catecholaminergic systems in diverse brain areas and allowed him to demonstrate the blockade of the uptake of tritiated noradrenaline by the tricyclic antidepressant imipramine and chemically related compounds [START_REF] Glowinski | Inhibition of uptake of [ 3 H]noradrenaline in intact rat brain by imipramine and structurally related compounds[END_REF]. This discovery paved the way for the later development of selective reuptake inhibitors for the treatment of depression. The years with Axelrod provided numerous discoveries about catecholamines, histamine, and other neurochemicals, and led to the publication of some twenty papers, many of becaming classics in Neuropharmacology. The article by [START_REF] Glowinski | Regional studies of catecholamines in the rat brain. I-The disposition of[END_REF] on regional differences in catecholamine uptake and turnover, which described a simple way of dissecting the brain for biochemical studies is in fact the most highly cited article ever published in the Journal of Neurochemistry (more than 5700 citations !). Indeed, the Journal of Neurochemistry was one of his favorite journals, he published 63 papers there, throughout his very productive scientific career (more than 600 original papers; Web of Science).

When Jacques returned to France in late 1965, he rapidly obtained a researcher position at INSERM, and Pr Fessard provided him with some space in his department.

At that time, the discipline of Neuropharmacology was a vision to be built into reality in France, and Jacques took on the task, leading to the success and national and international glory that we know. He attracted several young students from the Faculty of Sciences including Anne-Marie Thierry, Marie-Jo Besson, France Javoy, Francis Héry, as well as talented individuals from technical schools, André Chéramy and Gérard Blanc. Very soon he was also joined by clinicians who spent internships in his lab and by scientists from the pharmaceutical industry. Seymour Kety and Louis Sokoloff, who had become his friends when he was at the NIH, spent sabbaticals with him and helped to launch his lab further. The exceptional creativity of Jacques saw its pinnacle with the development of innovative approaches to measure neurotransmitter release in vivo, in the rat, cat and monkey, and in vitro (from brain slices and later cells in culture). The study of neurotransmitter synthesis and fine regulatory mechanisms in discrete brain areas in vivo allowed the demonstration of the preferential role of newly synthesized monoamines in neuromodulation [START_REF] Besson | Release of newly synthesized dopamine from dopamine-containing terminals in striatum of rat[END_REF][START_REF] Javoy | Dynamic characteristic of the "functional compartment" of dopamine in dopaminergic terminals of the rat striatum[END_REF]. At a more conceptual level, he developed the idea of three integrated brain systems, with executive (sensori-motor and cognitive), modulatory (monoamines, neuropeptides), and metabolic (glial cells) contributions, for his fully attended lectures at the Collège de France. Throughout these years, Jacques' laboratory, or "Glo's lab", welcomed many scientists in an enlarged convenient environment, with a multidisciplinary approach boasting a wide array of cutting edge technologies, including molecular and cellular neurophysiology, immunocytochemistry, cell culture, molecular pharmacology, and the thorough study of rat behavior. These extensive neuropharmacological approaches were applied not only to monoamines, but also to other neurotransmitters such as acetylcholine, neuropeptides (particularly substance P and enkephalins), glutamate and GABA. Over the years, major discoveries included (i) the identification of the mesocortical dopaminergic pathway, the characterization of its role in cognitive functions [START_REF] Thierry | Dopaminergic terminals in rat cortex[END_REF] and in the mechanisms of action of antipsychotics, (ii) the demonstration of dendritic release of dopamine in the substantia nigra and its importance in the regulation of nigrostriatal neurons by autoreceptors [START_REF] Nieoullon | Release of dopamine in vivo from cat substantia nigra[END_REF][START_REF] Chéramy | Dendritic release of dopamine in the substania nigra[END_REF], (iii) the key role of interactions between neurons and astrocytes for neuronal differentiation [START_REF] Denis-Donini | Glial heterogeneity may define the 3-dimensional shape of mouse mesencephalic dopaminergic neurons[END_REF], (iv) the role of gap junctions and connexins in astrocyte networks (Giaume et al., 1991), (v) the identification and characterization of multiple receptors for serotonin [START_REF] Gozlan | Identification of presynaptic serotonin autoreceptors using a new ligand : 3 H-PAT[END_REF], substance P [START_REF] Beaujouan | Different subtypes of tachykinin NK1 receptor binding sites are present in the rat brain[END_REF], without forgetting (vi) the analysis of the regulatory mechanisms of these various neurotransmission systems in validated animal models of brain diseases [START_REF] Agid | Hyperactivity of remaining dopaminergic neurons after partial destruction of nigro-striatal dopaminegic system in rat[END_REF].

In recognition of the major contributions of Jacques and his laboratory to Neuropharmacology, he was elected Professor at the Collège de France (chair of Neuropharmacology, 1982Neuropharmacology, -2006) ) and member of the French Academy of Sciences (1992). He participated in the executive board of INSERM (1979INSERM ( -1992) ) A man of conviction and dialogue, Jacques Glowinski worked throughout his career to establish efficient links between academic research, medicine, and the pharmaceutical industry. Many physicians, several who later became clinical department heads, were trained in his lab and were inspired by his humanistic concepts to revisit their approaches in neurology and psychiatry. As soon as he started his lab at the Collège de France, Jacques established close links with the pharmaceutical company Rhône-Poulenc (which later became Sanofi due to a merger/acquisition process). By hosting Rhône-Poulenc scientists in his Unit, he contributed to the development of the company's neuroscience research labs and participated in strategies targeted towards neuro-psychiatric diseases. In this respect, he was a visionary in France, promoting private-public interactions that were very rare at the time and required the courage to resist criticisms from the academic world.

Ironically, many of his early critics later followed his example. His open mindedness and humanistic vision led him to help his friend Bernard Esambert launch the Fédération pour la Recherche sur le Cerveau, that united several patient and family associations with private foundations to support Neuroscience research in France.

After his US experience, Jacques Glowinski's whole career was spent at the Collège de France, where he was elected to the key position of "Administrateur" (Director, 2000(Director, -2006)). As early as 1991, Jacques Glowinski was involved in the « Grand Projects » operation to renovate the Collège de France, for which André Miquel, Director at that time, entrusted him to lead. He was then able to undertake and successfully attain what had been his dream since his arrival at the place, to renovate and reorganize this prestigious institution whose buildings were in poor shape. The aim was to restore it to good conditions to host cutting edge research and to provide high level education open to a large audience, at the center of an intellectual life in sciences and humanities in France. It should be noted that the Collège de France is a unique institution, created in 1530 by King François the 1 st , to contrast with what was then perceived as a dogmatic Sorbonne. Its mission is and has always been to provide education that is open to all, without restrictive requirements and without the authority or obligation to deliver academic or professional degrees. For his successful undertaking, Jacques was acknowledged by the highest French official honors. In the process of leading these renovations, Jacques unraveled other facets of his personality, specifically his remarkable drawing skills and his steadfast passion for architecture, which led him to be called upon after 2006, when he was Professor Emeritus, to play a key role in the reorganization of the vast Paris-Saclay University campus for research and innovation. His many contributions at multiple levels now constitute an immense legacy, with a long-lasting impact on Neuroscience in France and beyond, on advocacy and organization of research. Jacques, our dear « Glo », was not only a world leading neuroscientist but also a visionary and caring man with an entrepreneurial spirit and a great personal warmth. This unique combination profoundly influenced those who met him, making him unforgettable. He will be deeply missed. May he rest in peace. Jacques Glowinski in the courtyard of the Collège de France during "his" renovation works

  Curious, bright, and hard-working, Jacques moved towards studying Pharmacy at the beginning of the sixties, and already showing a keen interest in brain research, he received a parallel training at the Faculty of Pharmacy and Faculty of Sciences at Paris University. On the occasion of an examination at the Faculty of Sciences where he presented his first research work carried out at the Pasteur Institute, on chemical synthesis of tritiated catecholamines, Jacques met Denise Albe-Fessard, professor of Neurophysiology. She proposed that he come and work at the Marey Institute, the top Parisian site for research in this area at the time, which was headed by her husband, Alfred Fessard, holder of the chair of Neurophysiology at the Collège de France. Strongly impressed by his energy, vivid intelligence and brightness, the Fessards (known respectfully as "Monsieur and Madame Fessard") pointed out to Jacques the promising development of a new discipline -Neuropharmacology -at the NIH in Bethesda, under the impetus of Seymour Kety, Irwin Kopin and Julius ("Julie") Alxelrod (who received the Nobel Prize for Physiology or Medicine in 1970). Contact was made,

  and received prestigious awards (Richard Lounsbery prize, 1986 ; Grand prix de la Fondation pour la Recherche Médicale 2002 ; Inserm Honour prize, 2005 ; Life Achievement Award of the European College of Neuropsychopharmacology, 2008, to name only a few). He was appointed President of the French Society for Neuroscience (1995-1999) and he participated in the launching of the European Neuroscience Association (later to become FENS).

Acknowledgements

The authors have no conflict of interest to declare. JA Girault was in Glowinski's lab in 1982-1985 and 1990-1999, M Hamon in 1968-1984, and B Scatton (former Vice-President of discovery research at Sanofi) collaborated with him in 1970-1976 and 2000-2008. The authors warmly thank Pr Christopher G. Goetz (Rush University Medical Center, Chicago IL60612) and Dr Fiona Francis (Institut du Fer à Moulin, UMR-S 1270, Inserm, Sorbonne Université, Paris) for careful editing and Dr Marie-Lou Kemel for picture courtesy.