high performance computing on graphics processing units: hgpu.org

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Flexible neuronal network simulation framework using code generation for NVidia CUDA

Thomas Nowotny

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Tags: Bioinformatics, Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia Quadro FX 5800, Poster

October 26, 2011 by hgpu

Evaluation of GPU Architectures Using Spiking Neural Networks

Vivek K. Pallipuram, Mohammad A. Bhuiyan, Melissa C. Smith

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Tags: ATI, ATI Radeon HD 5870, Computer science, Neural networks, nVidia, OpenCL, Optimization, Performance, Presentation, Tesla C2050

October 10, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

Flexible, high performance convolutional neural networks for image classification

Dan C. Ciresan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Benchmarking, Computer science, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580

October 5, 2011 by hgpu

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Li Liang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, OpenCL, Optimization

October 3, 2011 by hgpu

Simulating Biological-Inspired Spiking Neural Networks with OpenCL

Jorn Hoffmann, Karim El-Laithy, Frank Guttler, Martin Bogdan

Tags: Computer science, Data parallelism, Neural networks, OpenCL

August 18, 2011 by hgpu

Parallel Batch Training of the Self-Organizing Map Using OpenCL

Masahiro Takatsuka, Michael Bui

Tags: Computer science, Neural networks, OpenCL, Self-organizing map

August 18, 2011 by hgpu

Accelerated simulation of spiking neural networks using GPUs

Andreas K. Fidjeland, Murray P. Shanahan

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Tags: Biology, CUDA, Neural networks, nVidia, Tesla C1060

August 6, 2011 by hgpu

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

J.C. Chedjou, K. Kyamakya, U.A. Khan, M.A. Latif

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Tags: Cellular neural networks, CNN, Computational Engineering, Computer science, Differential equations, DSP, FPGA, Maxwell's equations, Neural networks, ODEs, Optimization, Ordinary differential equations, Partial differential equations, PDEs

August 2, 2011 by hgpu

FPGA Accelerated Simulation of Biologically Plausible Spiking Neural Networks

David B. Thomas, Wayne Luk

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Tags: Computer science, CUDA, FPGA, Neural networks, nVidia, nVidia GeForce GT 200, Performance

July 29, 2011 by hgpu

High-performance bankruptcy prediction model using Graphics Processing Units

Bernardete Ribeiro, Noel Lopes, Catarina Silva

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Tags: Finance, Neural networks, nVidia GeForce 8600 GT, nVidia GeForce GTX 280, Package

July 16, 2011 by hgpu

Computing spike-based convolutions on GPUs

Jayram Moorkanikara Nageswaran, Nikil Dutt, Yingxue Wang, Tobi Delbrueck

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

July 14, 2011 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Flexible neuronal network simulation framework using code generation for NVidia CUDA

Evaluation of GPU Architectures Using Spiking Neural Networks

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Flexible, high performance convolutional neural networks for image classification

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Simulating Biological-Inspired Spiking Neural Networks with OpenCL

Parallel Batch Training of the Self-Organizing Map Using OpenCL

Accelerated simulation of spiking neural networks using GPUs

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

FPGA Accelerated Simulation of Biologically Plausible Spiking Neural Networks

High-performance bankruptcy prediction model using Graphics Processing Units

Computing spike-based convolutions on GPUs

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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