high performance computing on graphics processing units: hgpu.org

Programming

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Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Konstantin Herb, Pol Welter

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Tags: BLAS, Computational Physics, Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla V100

August 22, 2021 by hgpu

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

Shandong Lao, Aaron Holt, Deepthi Vaidhynathan, Hariswaran Sitaraman, Christine M. Hrenya, Thomas Hauser

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Tags: cfd, CUDA, Fluid dynamics, HPC, nVidia, nVidia A100, Tesla V100

August 22, 2021 by hgpu

Better GPU Hash Tables

Muhammad A. Awad, Saman Ashkiani, Serban D. Porumbescu, Martín Farach-Colton, John D. Owens

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX Titan X

August 22, 2021 by hgpu

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Fabian Knorr, Peter Thoman, Thomas Fahringer

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, Package, SYCL, Tesla V100

August 8, 2021 by hgpu

Performance assessment of CUDA and OpenACC in large scale combustion simulations

Guillermo Oyarzun, Daniel Mira, Guillaume Houzeaux

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Tags: CUDA, nVidia, OpenACC, Performance, Physics, Tesla V100

August 8, 2021 by hgpu

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

Daniel Gerzhoy

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Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

August 8, 2021 by hgpu

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Jan Solanti, Michal Babej, Julius Ikkala, Vinod Kumar Malamal Vadakital, Pekka Jääskeläinen

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Tags: Computer science, GPU cluster, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package, Rendering, Tesla P100, Tesla V100

August 8, 2021 by hgpu

Effective GPU Sharing Under Compiler Guidance

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, LLVM, Neural networks, nVidia, Tesla P100, Tesla V100

July 25, 2021 by hgpu

StreamBlocks: A compiler for heterogeneous dataflow computing

Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL, Package, Performance

July 25, 2021 by hgpu

A method for decompilation of AMD GCN kernels to OpenCL

K.I. Mihajlenko, M.A. Lukin, A.S. Stankevich

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Tags: Compilers, Computer science, OpenCL, Package, Python

July 25, 2021 by hgpu

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Daouda Diakite, Nicolas Gac, Maxime Martelli

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Tags: Computed tomography, Computer science, CT, FPGA, HLS, Medicine, OpenCL, Tomography

July 18, 2021 by hgpu

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

Devon Callanan

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Tags: Computer science, FPGA, OpenCL, Security, Thesis

July 18, 2021 by hgpu

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

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

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

Better GPU Hash Tables

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Performance assessment of CUDA and OpenACC in large scale combustion simulations

On Efficient GPGPU Computing for Integrated Heterogeneous CPU-GPU Microprocessors

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Effective GPU Sharing Under Compiler Guidance

StreamBlocks: A compiler for heterogeneous dataflow computing

A method for decompilation of AMD GCN kernels to OpenCL

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Accelerating Regular-Expression Matching on FPGAs with High-Level Synthesis

Recent source codes

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

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