high performance computing on graphics processing units: hgpu.org

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Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Daniel Sanchez, David Lo, Richard M. Yoo, Jeremy Sugerman, Christos Kozyrakis

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques

October 17, 2011 by hgpu

Programming with Explicit Dependencies. A Framework for Portable Parallel Programming

Eva Burrows

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 250, Programming techniques, Sorting, Thesis

October 17, 2011 by hgpu

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

Andrew J. Martin

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 570, Thesis

October 17, 2011 by hgpu

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

D.P. Playne, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, GPU cluster, MPI, Numerical simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480

October 16, 2011 by hgpu

An Auto-tuned Method for Solving Large Tridiagonal Systems on the GPU

Andrew Davidson, Yao Zhang, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, nVidia GeForce GTX 470

October 16, 2011 by hgpu

GPU-to-CPU callbacks

Jeff A. Stuart, Michael Cox, John D. Owens

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

October 16, 2011 by hgpu

Data Layout Pruning on GPU

Xinbiao Gan, Zhiying Wang, Li Shen, Qi Zhu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280, Performance

October 16, 2011 by hgpu

Skeleton Programming for Heterogeneous GPU-based Systems

Usman Dastgeer

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C1060, Thesis

October 16, 2011 by hgpu

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Naoya Maruyama, Tatsuo Nomura, Kento Sato, Satoshi Matsuoka

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Tags: Computer science, CUDA, MPI, nVidia, Optimization, Package, Performance, Programming Languages, Programming techniques, Tesla M2050

October 15, 2011 by hgpu

Operating Systems Challenges for GPU Resource Management

Shinpei Kato, Scott Brandt, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenCL, Operating systems, Virtualization

October 15, 2011 by hgpu

Towards Utilizing Remote GPUs for CUDA Program Execution

Xiaonan Ji, Spencer Davis, Erikson Hardesty, Xu Liang, Sabuj Saha, Hai Jiang

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Networks, nVidia

October 15, 2011 by hgpu

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Shuai Che, Jeremy W. Sheaffer, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Performance

October 15, 2011 by hgpu

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

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Programming with Explicit Dependencies. A Framework for Portable Parallel Programming

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

An Auto-tuned Method for Solving Large Tridiagonal Systems on the GPU

GPU-to-CPU callbacks

Data Layout Pruning on GPU

Skeleton Programming for Heterogeneous GPU-based Systems

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Operating Systems Challenges for GPU Resource Management

Towards Utilizing Remote GPUs for CUDA Program Execution

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Recent source codes

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

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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