high performance computing on graphics processing units: hgpu.org

hgpu.org » Code generation

AnySL: efficient and portable shading for ray tracing

Ralf Karrenberg, Dmitri Rubinstein, Philipp Slusallek, Sebastian Hack

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, Code generation, Compilers, Computer science, nVidia, Package, Programming Languages, PTX, Raytracing, Rendering

September 13, 2011 by hgpu

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

Tiark Rompf, Martin Odersky

View

Download (PDF)

Tags: Code generation, Computer science, Optimization, Programming Languages, Software Engineering

September 11, 2011 by hgpu

High-performance SIMT code generation in an active visual effects library

Jay L.T. Cornwall, Lee Howes, Paul H.J. Kelly, Phil Parsonage, Bruno Nicoletti

View

Download (PDF)

Tags: Algorithms, Code generation, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Performance, Software Engineering, Visualization

September 11, 2011 by hgpu

MacroSS: macro-SIMDization of streaming applications

Amir H. Hormati, Yoonseo Choi, Mark Woh, Manjunath Kudlur, Rodric Rabbah, Trevor Mudge, Scott Mahlke

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, Optimization, Performance, Programming Languages

September 7, 2011 by hgpu

CUDA-level performance with python-level productivity for Gaussian mixture model applications

H. Cook, E. Gonina, S. Kamil, G. Friedland, D. Patterson, A. Fox

View

Download (PDF)

Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, OpenCL, Python

September 7, 2011 by hgpu

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

Allen Leung, Nicolas Vasilache, Benoit Meister, Muthu Baskaran, David Wohlford, Cedric Bastoul, Richard Lethin

View

Download (PDF)

Tags: Algorithms, Code generation, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 285, Programming Languages

August 24, 2011 by hgpu

JCudaMP: OpenMP/Java on CUDA

Georg Dotzler, Ronald Veldema, Michael Klemm

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 280, OpenMP, Programming Languages, Programming techniques

August 23, 2011 by hgpu

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Martin Sandrieser, Siegfried Benkner, Sabri Pllana

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, OpenMP, Presentation

August 22, 2011 by hgpu

Accelerating Haskell array codes with multicore GPUs

Manuel M.T. Chakravarty, Gabriele Keller, Sean Lee, Trevor L. McDonell, Vinod Grover

View

Download (PDF)

Tags: Code generation, Computer science, CUBLAS, CUDA, Data parallelism, nVidia, Performance, Programming Languages, Tesla T10

August 22, 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

Hybrid OpenCL: Enhancing OpenCL for Distributed Processing

Ryo Aoki, Shuichi Oikawa, Takashi Nakamura, Satoshi Miki

Tags: Code generation, Computer science, GPU cluster, MPI, OpenCL

July 22, 2011 by hgpu

HPCToolkit

Refining HPCToolkit for application performance analysis at exascale

Open Catalog of Best Practices for Modernization and Optimization

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Noarr Structures

Abstractions for C++ code optimizations in parallel high-performance applications

$3D-fractal-generators$

HiCCL: A hierarchical collective communications library with portable optimizations

HiCCL: A Hierarchical Collective Communication Library

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

AnySL: efficient and portable shading for ray tracing

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

High-performance SIMT code generation in an active visual effects library

MacroSS: macro-SIMDization of streaming applications

CUDA-level performance with python-level productivity for Gaussian mixture model applications

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

JCudaMP: OpenMP/Java on CUDA

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Accelerating Haskell array codes with multicore GPUs

Performance Comparison with OpenMP Parallelization for Multi-core Systems

Performance Debugging of GPGPU Applications with the Divergence Map

Hybrid OpenCL: Enhancing OpenCL for Distributed Processing

Recent source codes

HPCToolkit

Open Catalog of Best Practices for Modernization and Optimization

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

GPU-Smash: Compression abstraction library

Noarr Structures

3D-fractal-generators

SyncPerformance

VerCors: a verification toolset for verifying parallel and concurrent software

HiCCL: A hierarchical collective communications library with portable optimizations

Most viewed papers (last 30 days)