high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Hemant Shukla, Hsi-Yu Schive, Tak-Pong Woo, Tzihong Chiueh

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Physics, Rendering, Tesla C2050

December 10, 2011 by hgpu

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

Deepak Mathews Panickal

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Tags: ATI, ATI Radeon HD 5470, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Optimization, Tesla C2070, Thesis

December 9, 2011 by hgpu

Towards a complete FEM-based simulation toolkit on GPUs: Geometric Multigrid solvers

Markus Geveler, Dirk Ribbrock, Dominik Goddeke, Peter Zajac, Stefan Turek

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Tags: Benchmarking, CUDA, Differential equations, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 285, Partial differential equations, PDEs, Sparse matrix

December 7, 2011 by hgpu

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Alecio Pedro Delazari Binotto

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, OpenCL, Task scheduling, Thesis

December 5, 2011 by hgpu

GROPHECY: GPU performance projection from CPU code skeletons

Jiayuan Meng, Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas D. Uram

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Tags: Analytical model, Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance, Tesla C1060

December 5, 2011 by hgpu

GPU-Based Parallel Multi-objective Particle Swarm Optimization

You Zhou, Ying Tan

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce 9800 GT, Optimization

December 4, 2011 by hgpu

Comparison of CPML Implementations for the GPU-Accelerated FDTD Solver

J.I. Toivanen, T.P. Stefanski, N. Kuster, N. Chavannes

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Tags: Benchmarking, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Tesla C1060

December 3, 2011 by hgpu

On the design of architecture-aware algorithms for emerging applications

Seunghwa Kang

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Tags: Algorithms, Benchmarking, Biology, Cell processor, Computational biology, CUDA, Image processing, MapReduce, nVidia, Package, Tesla C1060, Thesis

December 2, 2011 by hgpu

An error correction solver for linear systems: Evaluation of mixed precision implementations

Hartwig Anzt, Vincent Heuveline, Bjorn Rocker

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Tags: Benchmarking, Computer science, CUDA, Mixed precision, nVidia, Tesla S1070

December 2, 2011 by hgpu

GPU Accelerated Dissipative Particle Dynamics with Parallel Cell-list Updating

Hao Wu, Junbo Xu, Shengfei Zhang, Hao Wen

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Tags: Algorithms, Benchmarking, Chemistry, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 285, Optimization

November 30, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Numerical Precision and Benchmarking Very-High-Order Integration of Particle Dynamics on GPU Accelerators

K.A. Hawick, D.P. Playne, M.G.B. Johnson

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Tags: Algorithms, Benchmarking, Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla C2070

November 27, 2011 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

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

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

Towards a complete FEM-based simulation toolkit on GPUs: Geometric Multigrid solvers

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

GROPHECY: GPU performance projection from CPU code skeletons

GPU-Based Parallel Multi-objective Particle Swarm Optimization

Comparison of CPML Implementations for the GPU-Accelerated FDTD Solver

On the design of architecture-aware algorithms for emerging applications

An error correction solver for linear systems: Evaluation of mixed precision implementations

GPU Accelerated Dissipative Particle Dynamics with Parallel Cell-list Updating

Applications Performance on GPGPUs with the Fermi Architecture

Numerical Precision and Benchmarking Very-High-Order Integration of Particle Dynamics on GPU Accelerators

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

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

Agentic Code Optimization via Compiler-LLM Cooperation

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