high performance computing on graphics processing units: hgpu.org

Eduardo Cesar, Robert Mijacovic, Carmen Navarrete, Carla Guillien, Siegfried Benkner, Martin Sandrieser, Enes Bajrovic, Laurent Morin, Gertvjola Saveta, Anna Sikora

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Tags: Computer science, MPI, OpenCL, Performance

September 19, 2015 by hgpu

Autotuning Wavefront Patterns for Heterogeneous Architectures

Siddharth Mohanty

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Performance, Thesis

September 19, 2015 by hgpu

CLTune: A Generic Auto-Tuner for OpenCL Kernels

Cedric Nugteren, Valeriu Codreanu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel HD 5100, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Performance, Tesla K40

September 17, 2015 by hgpu

A Performance Comparison of Algebraic Multigrid Preconditioners on CPUs, GPUs, and Xeon Phis

K. Rupp, J. Weinbub, F. Rudolf, A. Morhammer, T. Grasser, A. Jungel

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Tags: AMD FirePro W9100, ATI, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, OpenMP, Performance, Tesla K20

September 9, 2015 by hgpu

Boosting Java Performance using GPGPUs

James Clarkson, Christos Kotselidis, Gavin Brown, Mikel Lujan

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla K20

August 28, 2015 by hgpu

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 980, Performance

August 24, 2015 by hgpu

Optimizing OpenCL Local Work Group Size With Machine Learning

Markus Schlafli

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Tags: ATI, ATI Radeon HD 7850, Computer science, Machine learning, OpenCL, Performance, PTX

August 18, 2015 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

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

Efficient Simulation Techniques for Large-Scale Applications

Adaptive and Transparent Cache Bypassing for GPUs

Automatic Online Tuning (AutoTune): Fully Extended Analysis

Autotuning Wavefront Patterns for Heterogeneous Architectures

CLTune: A Generic Auto-Tuner for OpenCL Kernels

A Performance Comparison of Algebraic Multigrid Preconditioners on CPUs, GPUs, and Xeon Phis

Boosting Java Performance using GPGPUs

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Optimizing OpenCL Local Work Group Size With Machine Learning

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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