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Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

George Ungureanu

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Heterogeneous systems, Image processing, nVidia, Thesis

September 25, 2013 by hgpu

A streaming model for nested data parallelism

Frederik M. Madsen

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Thesis

September 21, 2013 by hgpu

Transparent CPU-GPU Collaboration for Data-Parallel Kernels on Heterogeneous Systems

J. Lee, M. Samadi, Y. Park, S. Mahlke

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Tags: Data parallelism, Heterogeneous systems, nVidia, nVidia GeForce GTX 560, nVidia Quadro 600, OpenCL

September 5, 2013 by hgpu

NOVA: A Functional Language for Data Parallelism

Alexander Collins, Dominik Grewe, Vinod Grover, Sean Lee, Adriana Susnea

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Tags: Compilers, Computer science, CUDA, Data parallelism, High-level Languages, nVidia, nVidia GeForce GTX 480

August 1, 2013 by hgpu

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

Sivaramakrishnan Kasiviswanathan

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Tags: Algorithms, Computer science, Data parallelism, Matrix multiplication, nVidia, OpenCL, Tesla K20

July 19, 2013 by hgpu

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

George Zaki

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Tags: Algorithms, Code generation, Computational Engineering, CUDA, Data parallelism, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, Signal processing, Thesis

July 12, 2013 by hgpu

Exploiting Data Parallelism in the yConvex Hypergraph Algorithm for Image Representation using GPGPUs

Saurabh Jha, Tejaswi Agarwal, B. Rajesh Kanna

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Image processing, nVidia, nVidia GeForce GT 310 M

July 10, 2013 by hgpu

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

Ana Balevic

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 1, 2013 by hgpu

String Algorithm on GPGPU

Ong Wen Mei

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Tags: Algorithms, Bloom filter, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GT 530, nVidia Quadro FX 4000, String matching, Thesis

June 25, 2013 by hgpu

Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods

Xavier Andrade, Alan Aspuru-Guzik

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Source codes

Tags: ATI, ATI Radeon HD 7970, Computational Physics, Condensed matter, Data parallelism, nVidia, OpenCL, Package, Physics, Tesla K20

June 14, 2013 by hgpu

Job Parallelism using Graphical Processing Unit individual Multi-Processors and Highly Localised Memory

D. P. Playne, K. A. Hawick

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Tesla M2075

May 29, 2013 by hgpu

An implementation of level set based topology optimization using GPU

D. Herrero, J. Martinez, P. Marti

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Tags: Computational Complexity, CUDA, Data parallelism, FEM, Finite element method, Image processing, nVidia, Tesla C2070

May 19, 2013 by hgpu

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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high performance computing on graphics processing units: hgpu.org

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

A streaming model for nested data parallelism

Transparent CPU-GPU Collaboration for Data-Parallel Kernels on Heterogeneous Systems

NOVA: A Functional Language for Data Parallelism

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

Exploiting Data Parallelism in the yConvex Hypergraph Algorithm for Image Representation using GPGPUs

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

String Algorithm on GPGPU

Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods

Job Parallelism using Graphical Processing Unit individual Multi-Processors and Highly Localised Memory

An implementation of level set based topology optimization using GPU

Recent source codes

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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