Au cours du développement, les axones des cellules ganglionnaires de la rétine (CGRs) voyagent sur de longues distances pour établir des connexions avec leurs cellules cibles. La navigation des cônes de croissance est guidée par différentes molécules chimiotropiques présentes dans leur environnement. Les endocannabinoïdes (eCB) sont d’importants neuromodulateurs qui régulent de manière rétrograde la fonction de nombreuses synapses du cerveau. Ils agissent principalement par le biais de leurs récepteurs liés à une protéine Gi/o CB1 (CB1R) et CB2 (CB2R). La présence des eCBs durant le stade fœtal et la période postnatale suggère leur implication dans des événements régulant le développement du système nerveux. Cette thèse confirme l’expression des récepteurs aux cannabinoïdes CB1 et CB2 ainsi que l’enzyme dégradant les eCBs lors du développement embryonnaire et perinatal des CGRs et de la voie rétinothalamique in vivo. La manipulation pharmacologique de l’activité de CB1R et CB2R réorganise la morphologie du cône de croissance des CGRs et des neurones corticaux in vitro. De plus, la stimulation locale avec un agoniste de CB1R ou de CB2R modifie le comportement du cône de croissance entraînant sa répulsion. CB1R et CB2R modulent par le biais de la voie de signalisation AMPc/PKA, la mobilisation de DCC à la membrane plasmique. Par ailleurs, les résultats de cette recherche démontrent également l’implication de CB1R et CB2R dans la ségrégation des projections ipsi- et controlatérales et le développement de la voie rétinothalamique. / Following differentiation, retinal ganglion cell (RGC) axons, tipped at their distal end by the growth cone (GC), navigate through relatively long distances in a highly directed manner in order to establish functional synapses with thalamic and superior colliculus (SC) neurons. This is achieved with the help of extracellular guidance molecules which steer RGC axon growth by regulating GC morphology by means of attractive and/or repulsive mechanisms. In the adult brain, endocannabinoids (eCBs) exert an important neuromodulatory function by acting as retrograde messengers to regulate the function of many synapses. Endocannabinoids act mainly via their Gi/o protein coupled receptors CB1 (CB1R) and CB2 (CB2R). Due to their presence at the fetal and early postnatal periods, it has been proposed that eCBs and their receptors might be involved in several developmental events, such as cell proliferation and migration, axon guidance and synaptogenesis. We observed that during early postnatal development, components of the eCB system are expressed along the visual pathway (the optic chiasm, the lateral geniculate nucleus and the SC). To assess the implication of the eCB system, in vitro, embryonic retinal explant and primary neuron cultures were treated with pharmacological agonists and inverse agonists of CB1R and CB2R. These experiments demonstrated that these cannabinoid receptors modify the GC’s morphology. Most importantly, CB1R and CB2R act through the cAMP/PKA pathway to modulate the presence of DCC at the plasma membrane. In vivo, CB1R and CB2R play a major role and the absence of either one of them induces a decrease in eye-specific segregation of retinal projections. These results show an implication of CB1R and CB2R during RGC growth and retinothalamic development.

Au cours du développement, les axones des cellules ganglionnaires de la rétine (CGRs) voyagent sur de longues distances pour établir des connexions avec leurs cellules cibles. La navigation des cônes de croissance est guidée par différentes molécules chimiotropiques présentes dans leur environnement. Les endocannabinoïdes (eCB) sont d’importants neuromodulateurs qui régulent de manière rétrograde la fonction de nombreuses synapses du cerveau. Ils agissent principalement par le biais de leurs récepteurs liés à une protéine Gi/o CB1 (CB1R) et CB2 (CB2R). La présence des eCBs durant le stade fœtal et la période postnatale suggère leur implication dans des événements régulant le développement du système nerveux. Cette thèse confirme l’expression des récepteurs aux cannabinoïdes CB1 et CB2 ainsi que l’enzyme dégradant les eCBs lors du développement embryonnaire et perinatal des CGRs et de la voie rétinothalamique in vivo. La manipulation pharmacologique de l’activité de CB1R et CB2R réorganise la morphologie du cône de croissance des CGRs et des neurones corticaux in vitro. De plus, la stimulation locale avec un agoniste de CB1R ou de CB2R modifie le comportement du cône de croissance entraînant sa répulsion. CB1R et CB2R modulent par le biais de la voie de signalisation AMPc/PKA, la mobilisation de DCC à la membrane plasmique. Par ailleurs, les résultats de cette recherche démontrent également l’implication de CB1R et CB2R dans la ségrégation des projections ipsi- et controlatérales et le développement de la voie rétinothalamique. / Following differentiation, retinal ganglion cell (RGC) axons, tipped at their distal end by the growth cone (GC), navigate through relatively long distances in a highly directed manner in order to establish functional synapses with thalamic and superior colliculus (SC) neurons. This is achieved with the help of extracellular guidance molecules which steer RGC axon growth by regulating GC morphology by means of attractive and/or repulsive mechanisms. In the adult brain, endocannabinoids (eCBs) exert an important neuromodulatory function by acting as retrograde messengers to regulate the function of many synapses. Endocannabinoids act mainly via their Gi/o protein coupled receptors CB1 (CB1R) and CB2 (CB2R). Due to their presence at the fetal and early postnatal periods, it has been proposed that eCBs and their receptors might be involved in several developmental events, such as cell proliferation and migration, axon guidance and synaptogenesis. We observed that during early postnatal development, components of the eCB system are expressed along the visual pathway (the optic chiasm, the lateral geniculate nucleus and the SC). To assess the implication of the eCB system, in vitro, embryonic retinal explant and primary neuron cultures were treated with pharmacological agonists and inverse agonists of CB1R and CB2R. These experiments demonstrated that these cannabinoid receptors modify the GC’s morphology. Most importantly, CB1R and CB2R act through the cAMP/PKA pathway to modulate the presence of DCC at the plasma membrane. In vivo, CB1R and CB2R play a major role and the absence of either one of them induces a decrease in eye-specific segregation of retinal projections. These results show an implication of CB1R and CB2R during RGC growth and retinothalamic development.

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Achieving high computation efficiency, in terms of Cycles per Instruction (CPI), for high-performance computing kernels is an interesting and challenging research area. Dense Linear Algebra (DLA) computation is a representative high-performance computing ap- plication, which is used, for example, in LU and QR factorizations. Unfortunately, mod- ern off-the-shelf microprocessors fall significantly short of achieving theoretical lower bound in CPI for high performance computing applications. In this thesis, we perform an in-depth analysis of the available parallelisms and propose suitable algorithmic and architectural variation to significantly improve the computation efficiency. There are two standard approaches for improving the computation effficiency, first, to perform application-specific architecture customization and second, to do algorithmic tuning. In the same manner, we first perform a graph-based analysis of selected DLA kernels. From the various forms of parallelism, thus identified, we design a custom processing element for improving the CPI. The processing elements are used as building blocks for a commercially available Coarse-Grained Reconfigurable Architecture (CGRA). By per- forming detailed experiments on a synthesized CGRA implementation, we demonstrate that our proposed algorithmic and architectural variations are able to achieve lower CPI compared to off-the-shelf microprocessors. We also benchmark against state-of-the-art custom implementations to report higher energy-performance-area product. DLA computations are encountered in many engineering and scientific computing ap- plications ranging from Computational Fluid Dynamics (CFD) to Eigenvalue problem. Traditionally, these applications are written in highly tuned High Performance Comput- ing (HPC) software packages like Linear Algebra Package (LAPACK), and/or Scalable Linear Algebra Package (ScaLAPACK). The basic building block for these packages is Ba- sic Linear Algebra Subprograms (BLAS). Algorithms pertaining LAPACK/ScaLAPACK are written in-terms of BLAS to achieve high throughput. Despite extensive intellectual efforts in development and tuning of these packages, there still exists a scope for fur- ther tuning in this packages. In this thesis, we revisit most prominent and widely used compute bound algorithms like GMM for further exploitation of Instruction Level Parallelism (ILP). We further look into LU and QR factorizations for generalizations and exhibit higher ILP in these algorithms. We first accelerate sequential performance of the algorithms in BLAS and LAPACK and then focus on the parallel realization of these algorithms. Major contributions in the algorithmic tuning in this thesis are as follows: Algorithms: We present graph based analysis of General Matrix Multiplication (GMM) and discuss different types of parallelisms available in GMM We present analysis of Givens Rotation based QR factorization where we improve GR and derive Column-wise GR (CGR) that can annihilate multiple elements of a column of a matrix simultaneously. We show that the multiplications in CGR are lower than GR We generalize CGR further and derive Generalized GR (GGR) that can annihilate multiple elements of the columns of a matrix simultaneously. We show that the parallelism exhibited by GGR is much higher than GR and Householder Transform (HT) We extend generalizations to Square root Free GR (also knows as Fast Givens Rotation) and Square root and Division Free GR (SDFG) and derive Column-wise Fast Givens, and Column-wise SDFG . We also extend generalization for complex matrices and derive Complex Column-wise Givens Rotation Coarse-grained Recon gurable Architectures (CGRAs) have gained popularity in the last decade due to their power and area efficiency. Furthermore, CGRAs like REDEFINE also exhibit support for domain customizations. REDEFINE is an array of Tiles where each Tile consists of a Compute Element and a Router. The Routers are responsible for on-chip communication, while Compute Elements in the REDEFINE can be domain customized to accelerate the applications pertaining to the domain of interest. In this thesis, we consider REDEFINE base architecture as a starting point and we design Processing Element (PE) that can execute algorithms in BLAS and LAPACK efficiently. We perform several architectural enhancements in the PE to approach lower bound of the CPI. For parallel realization of BLAS and LAPACK, we attach this PE to the Router of REDEFINE. We achieve better area and power performance compared to the yesteryear customized architecture for DLA. Major contributions in architecture in this thesis are as follows: Architecture: We present design of a PE for acceleration of GMM which is a Level-3 BLAS operation We methodically enhance the PE with different features for improvement in the performance of GMM For efficient realization of Linear Algebra Package (LAPACK), we use PE that can efficiently execute GMM and show better performance For further acceleration of LU and QR factorizations in LAPACK, we identify macro operations encountered in LU and QR factorizations, and realize them on a reconfigurable data-path resulting in 25-30% lower run-time