high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

CU2CL: A CUDA-to-OpenCL Translator for Multi-and Many-core Architectures

Gabriel Martinez, Wu-chun Feng, Mark Gardner

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 280, OpenCL

September 24, 2011 by hgpu

Integrated Framework for Heterogeneous Embedded Platforms Using OpenCL

Kulin V. Seth

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Tags: Benchmarking, Computer science, DSP, Embedded high-performance computing, Heterogeneous systems, OpenCL, Optimization, Thesis

September 23, 2011 by hgpu

Embedding OpenCL in C++ for Expressive GPU Programming

Orion Lawlor

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Tags: ATI, ATI Radeon HD 6850, Benchmarking, Code generation, Computer science, GLSL, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 460 M, nVidia GeForce GTX 580, OpenCL, OpenGL, Package

September 23, 2011 by hgpu

Acceleration of Functional Validation Using GPGPU

Lalith Suresh, Navaneeth Rameshan, M. S. Gaur, Mark Zwolinski, Vijay Laxmi

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Tags: Algorithms, Benchmarking, Computer science, Electronic design automation, nVidia, nVidia Quadro FX 1700, Tesla C870

September 23, 2011 by hgpu

Orchestration by approximation: mapping stream programs onto multicore architectures

Sardar M. Farhad, Yousun Ko, Bernd Burgstaller, Bernhard Scholz

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Tags: Algorithms, Benchmarking, Compilers, Computer science, Optimization, Performance, Programming Languages

September 23, 2011 by hgpu

Quantifying NUMA and contention effects in multi-GPU systems

Kyle Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla M2070

September 23, 2011 by hgpu

Reducing branch divergence in GPU programs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Programming Languages

September 22, 2011 by hgpu

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Ashwin Prasad, Jayvant Anantpur, R. Govindarajan

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Tags: Benchmarking, Clustering, Computer science, CUDA, Data parallelism, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, Optimization

September 20, 2011 by hgpu

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

Wing-kei S. Yu, Ruirui Huang, Sarah Q. Xu, Sung-En Wang, Edwin Kan, G. Edward Suh

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Tags: Benchmarking, Computer science, Memory, nVidia, Performance

September 20, 2011 by hgpu

CuMAPz: a tool to analyze memory access patterns in CUDA

Yooseong Kim, Aviral Shrivastava

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory, nVidia, Performance, Tesla C1060

September 20, 2011 by hgpu

Stream computing on graphics hardware

Ian Buck

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Tags: Algorithms, ATI, ATI Radeon X800 XT, Benchmarking, Brook, Compilers, Computer science, nVidia, nVidia GeForce 6800, Review, Thesis

September 19, 2011 by hgpu

Fast Mersenne prime testing on the GPU

Andrew Thall

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Tags: Algorithms, Benchmarking, CUDA, Mathematical Software, Mathematics, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla C2050

September 15, 2011 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

CU2CL: A CUDA-to-OpenCL Translator for Multi-and Many-core Architectures

Integrated Framework for Heterogeneous Embedded Platforms Using OpenCL

Embedding OpenCL in C++ for Expressive GPU Programming

Acceleration of Functional Validation Using GPGPU

Orchestration by approximation: mapping stream programs onto multicore architectures

Quantifying NUMA and contention effects in multi-GPU systems

Reducing branch divergence in GPU programs

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

CuMAPz: a tool to analyze memory access patterns in CUDA

Stream computing on graphics hardware

Fast Mersenne prime testing on the GPU

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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