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Power, Energy and Speed of Embedded and Server Multi-Cores applied to Distributed Simulation of Spiking Neural Networks: ARM in NVIDIA Tegra vs Intel Xeon quad-cores

Pier Stanislao Paolucci, Roberto Ammendola, Andrea Biagioni, Ottorino Frezza, Francesca Lo Cicero, Alessandro Lonardo, Michele Martinelli, Elena Pastorelli, Francesco Simula, Piero Vicini

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Tags: ARM, Computer science, MPI, Neural networks, Neurons and Cognition, nVidia, STDP

May 15, 2015 by hgpu

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

Jayram Moorkanikara M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alexander V. Veidenbaum

Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

November 13, 2010 by hgpu

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Jayram M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alex Veidenbaum

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Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

November 6, 2010 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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