high performance computing on graphics processing units: hgpu.org

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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

Synthesis of Platform Architectures from OpenCL Programs

Muhsen Owaida, Nikolaos Bellas, Konstantis Daloukas, Christos D. Antonopoulos

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Tags: Code generation, Compilers, Computer science, Electronic design automation, Embedded high-performance computing, FPGA, Heterogeneous systems, OpenCL

May 21, 2011 by hgpu

Compile-time GPU memory access optimizations

Gert-Jan van den Braak, Bart Mesman, Henk Corporaal

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Optimization, Programming techniques

May 17, 2011 by hgpu

GPU-S2S: A Compiler for Source-to-Source Translation on GPU

Dan Li, Haijun Cao, Xiaoshe Dong, Bao Zhang

Tags: Code generation, Compilers, Computer science, CUDA, High-level Languages, nVidia

April 23, 2011 by hgpu

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

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

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

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high performance computing on graphics processing units: hgpu.org

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

Synthesis of Platform Architectures from OpenCL Programs

Compile-time GPU memory access optimizations

GPU-S2S: A Compiler for Source-to-Source Translation on GPU

Recent source codes

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

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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