high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

uBench: Performance Impact of CUDA Block Geometry

Yuri Torres, Arturo Gonzalez, Diego R. Llanos

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

January 3, 2013 by hgpu

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

Liam Kiemele

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2075, Thesis

December 20, 2012 by hgpu

An Automatic Host and Device Memory Allocation Method for OpenMPC

Hiroaki Uchiyama, Tomoaki Tsumura, Hiroshi Matsuo

View

Download (PDF)

Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenMP, Performance, Tesla C1060

December 20, 2012 by hgpu

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Shoaib Ashraf Kamil

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 16, 2012 by hgpu

Vectorized Higher Order Finite Difference Kernels

Gerhard Zumbusch

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 6990, ATI Radeon HD 7970, Computer science, Finite difference, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C2050, Tesla K20

December 10, 2012 by hgpu

Neither More Nor Less: Optimizing Thread-level Parallelism for GPGPUs

Onur Kayiran, Adwait Jog, Mahmut T. Kandemir, Chita R. Das

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance

December 10, 2012 by hgpu

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Tim Cramer, Dirk Schmidl, Michael Klemm, Dieter an Mey

View

Download (PDF)

Tags: Benchmarking, Computer science, Intel, Intel Phi, OpenMP, Performance

December 8, 2012 by hgpu

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Tiark Rompf

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software Engineering, Tesla C2050, Thesis

December 8, 2012 by hgpu

FusionSim: Characterizing the Performance Benefits of Fused CPU/GPU Systems

Vitaly Zakharenko

View

Download (PDF)

Source codes

Tags: AMD Fusion, Analytical model, Benchmarking, Computer science, Package, Performance, Thesis

December 4, 2012 by hgpu

Characterization and Performance Analysis for 3D Benchmarks

Joseph Issa

View

Download (PDF)

Tags: Analytical model, ATI, ATI Radeon HD 3470, Benchmarking, Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9400 GT, nVidia GeForce 9500 GT, Performance

November 25, 2012 by hgpu

Location-based Matching in Publish/Subscribe Revisited

Mohammad Sadoghi, Hans-Arno Jacobsen

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 460, Performance

November 25, 2012 by hgpu

Dataflow-driven GPU performance projection for multi-kernel transformations

Jiayuan Meng, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran

View

Download (PDF)

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

November 20, 2012 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

* * *

high performance computing on graphics processing units: hgpu.org

uBench: Performance Impact of CUDA Block Geometry

KFusion: Obtaining Modularity and Performance with Regards to General Purpose GPU Computing and Co-processors

An Automatic Host and Device Memory Allocation Method for OpenMPC

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Vectorized Higher Order Finite Difference Kernels

Neither More Nor Less: Optimizing Thread-level Parallelism for GPGPUs

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

FusionSim: Characterizing the Performance Benefits of Fused CPU/GPU Systems

Characterization and Performance Analysis for 3D Benchmarks

Location-based Matching in Publish/Subscribe Revisited

Dataflow-driven GPU performance projection for multi-kernel transformations

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

Most viewed papers (last 30 days)