high performance computing on graphics processing units: hgpu.org

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Implementing the PGI Accelerator model

Michael Wolfe

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization, Programming Languages, Tesla C1060, Tesla S1070

August 23, 2011 by hgpu

Compiling Python to a hybrid execution environment

Rahul Garg, Jose Nelson Amaral

Tags: ATI, ATI CAL, BLAS, Compilers, Computer science, OpenCL, Python

August 21, 2011 by hgpu

Sponge: portable stream programming on graphics engines

Amir H. Hormati, Mehrzad Samadi, Mark Woh, Trevor Mudge, Scott Mahlke

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization, Performance, Programming Languages

August 21, 2011 by hgpu

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Jing Guo, Jeyarajan Thiyagalingam, Sven-Bodo Scholz

Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Programming Languages

August 21, 2011 by hgpu

Performance Comparison with OpenMP Parallelization for Multi-core Systems

Chao-Tung Yang, Tzu-Chieh Chang, Hsien-Yi Wang, William C.C. Chu, Chih-Hung Chang

Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Fortran, nVidia, OpenCL, OpenMP, Performance

August 8, 2011 by hgpu

Performance Debugging of GPGPU Applications with the Divergence Map

Bruno Coutinho, Diogo Sampaio, Fernando M. Q. Pereira, Wagner Meira Jr.

Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, PTX

August 1, 2011 by hgpu

A refactoring tool to extract GPU kernels

Kostadin Damevski, Madhan Muralimanohar

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Presentation

July 22, 2011 by hgpu

GLOpenCL: OpenCL support on hardware- and software-managed cache multicores

Konstantis Daloukas, Christos D. Antonopoulos, Nikolaos Bellas

Tags: Code generation, Compilers, Computer science, Heterogeneous systems, OpenCL

July 22, 2011 by hgpu

MATLAB Parallelization through Scalarization

Chun-Yu Shei, Adarsh Yoga, Madhav Ramesh, Arun Chauhan

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Tags: Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060

July 11, 2011 by hgpu

Many-core parallel computing – Can compilers and tools do the heavy lifting?

W.-m.W. Hwu

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Tags: Compilers, Computer science, CUDA, Image processing, nVidia, Presentation, Review

July 10, 2011 by hgpu

A compiler for high performance computing with many-core accelerators

Naohito Nakasato, Jun Makino

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Tags: ATI, ATI CAL, ATI IL, Compilers, Computer science, RV770

June 15, 2011 by hgpu

Multilevel Granularity Parallelism Synthesis on FPGAs

Alexandros Papakonstantinou, Yun Liang, John A. Stratton, Karthik Gururaj, Deming Chen, Wen-Mei W. Hwu, Jason Cong

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Tags: Code generation, Compilers, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 9800 GX2

May 21, 2011 by hgpu

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

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high performance computing on graphics processing units: hgpu.org

Implementing the PGI Accelerator model

Compiling Python to a hybrid execution environment

Sponge: portable stream programming on graphics engines

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Performance Comparison with OpenMP Parallelization for Multi-core Systems

Performance Debugging of GPGPU Applications with the Divergence Map

A refactoring tool to extract GPU kernels

GLOpenCL: OpenCL support on hardware- and software-managed cache multicores

MATLAB Parallelization through Scalarization

Many-core parallel computing – Can compilers and tools do the heavy lifting?

A compiler for high performance computing with many-core accelerators

Multilevel Granularity Parallelism Synthesis on FPGAs

Recent source codes

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

Most viewed papers (last 30 days)