high performance computing on graphics processing units: hgpu.org

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On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Blake Koop

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Tags: CUDA, Fluid dynamics, nVidia, Performance, Tesla C2070

July 14, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Understanding the SIMD Efficiency of Graph Traversal on GPU

Yichao Cheng, Hong An, Zhitao Chen, Feng Li, Zhaohui Wang, Xia Jiang, Yi Peng

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C2050

July 10, 2014 by hgpu

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Hasse Lovgren

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Tags: ATI, ATI Radeon HD 5870, Computer science, Mathematics, Neural networks, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Tesla C1060, Thesis

July 9, 2014 by hgpu

On Static Timing Analysis of GPU Kernels

Vesa Hirvisalo

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Tags: Computer science, OpenCL, Performance, Timing analysis

July 4, 2014 by hgpu

SIMD Implementation of a Multiplicative Schwarz Smoother for a Multigrid Poisson Solver on an Intel Xeon Phi Coprocessor

Masatoshi Kawai, Takeshi Iwashita, Hiroshi Nakashima

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Tags: Computer science, Intel Xeon Phi, Performance, Poisson equation

July 4, 2014 by hgpu

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Shahzeb Siddiqui, Saber Feki

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Tags: Computer science, CUDA, nVidia, OpenACC, Performance, Tesla K20

July 3, 2014 by hgpu

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Langshi Chen, Serge Petiton, Leroy Drummond, Maxime Hugues

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla K20

July 3, 2014 by hgpu

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra

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Tags: Computer science, Linear Algebra, nVidia, Performance, Tesla K20, Tesla K40, Tesla M2090

July 1, 2014 by hgpu

Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Robrecht Dewaele

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Package, Performance, Thesis

June 28, 2014 by hgpu

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Pawel Gepner, Victor Gamayunov, David L. Fraser, Eric Houdard, Ludovic Sauge, Damien Declat, Mathieu Dubois

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Tags: Algorithms, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, Performance

June 28, 2014 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

See all packages

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high performance computing on graphics processing units: hgpu.org

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Benchmarking the Memory Hierarchy of Modern GPUs

Understanding the SIMD Efficiency of Graph Traversal on GPU

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

On Static Timing Analysis of GPU Kernels

SIMD Implementation of a Multiplicative Schwarz Smoother for a Multigrid Poisson Solver on an Intel Xeon Phi Coprocessor

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Mixed-precision Orthogonalization Scheme and Adaptive Step Size for CA-GMRES on GPUs

Performance and Efficiency Analysis of Modern Accelerators: Fine-Grained Parallelism on the Intel Xeon Phi

Evaluation of DGEMM Implementation on Intel Xeon Phi Coprocessor

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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