high performance computing on graphics processing units: hgpu.org

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Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

Perhaad Mistry, Yash Ukidave, Dana Schaa, David Kaeli

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Tags: APU, ATI, ATI Radeon HD 7850, ATI Radeon HD 7970, Benchmarking, Computer science, Computer vision, Heterogeneous systems, OpenCL, Performance

April 22, 2013 by hgpu

Zero-copy I/O processing for low-latency GPU computing

Shinpei Kato, Jason Aumiller, Scott Brandt

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Tags: Algorithms, Benchmarking, CUDA, Data parallelism, nVidia, Plasma physics

April 16, 2013 by hgpu

Improving Performance Portability in OpenCL Programs

Yao Zhang, Mark Sinclair II, Andrew A. Chien

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Tags: APU, ATI, Benchmarking, Computer science, FFT, nVidia, OpenCL, Tesla C2050

March 26, 2013 by hgpu

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Junjie Lai, Andre Seznec

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 680, Optimization, Performance

February 22, 2013 by hgpu

Hybrid parallel programming – evaluation of OpenACC

Leonardo Piletti Chatain

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Tags: Benchmarking, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 480, OpenACC, Thesis

February 15, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 by hgpu

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

S. J. Pennycook, C. J. Hughes, M. Smelyanskiy, S. A. Jarvis

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Tags: Algorithms, Benchmarking, Computer science, Intel, Intel Phi, Molecular dynamics

February 14, 2013 by hgpu

Interleaving and Lock-Step Semantics for Analysis and Verification of GPU Kernels

Peter Collingbourne, Alastair F. Donaldson, Jeroen Ketema, Shaz Qadeer

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce 9400 M, OpenCL, Package

January 15, 2013 by hgpu

Evaluating Reconfigurable Dataflow Computing Using the Himeno Benchmark

Yukinori Sato, Yasushi Inoguchi, Wayne Luk, Tadao Nakamura

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Tesla M2050

January 11, 2013 by hgpu

uBench: Performance Impact of CUDA Block Geometry

Yuri Torres, Arturo Gonzalez, Diego R. Llanos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

January 3, 2013 by hgpu

Floating Point Arithmetic for Transport Triggered Architectures

Timo Tapani Viitanen

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Tags: Algorithms, Benchmarking, Computer science, FPGA, OpenCL, Thesis

December 30, 2012 by hgpu

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Tim Cramer, Dirk Schmidl, Michael Klemm, Dieter an Mey

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Tags: Benchmarking, Computer science, Intel, Intel Phi, OpenMP, Performance

December 8, 2012 by hgpu

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

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high performance computing on graphics processing units: hgpu.org

Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

Zero-copy I/O processing for low-latency GPU computing

Improving Performance Portability in OpenCL Programs

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Hybrid parallel programming – evaluation of OpenACC

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

Interleaving and Lock-Step Semantics for Analysis and Verification of GPU Kernels

Evaluating Reconfigurable Dataflow Computing Using the Himeno Benchmark

uBench: Performance Impact of CUDA Block Geometry

Floating Point Arithmetic for Transport Triggered Architectures

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Recent source codes

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

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