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Exploring GPGPU Acceleration of Process-Oriented Simulations

Frederick R.M. Barnes, Thomas Pressnell, Brendan Le Foll

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Package, Programming Languages

November 26, 2013 by hgpu

A Methodology for Translating C-Programs to OpenCL

Krishnahari Thouti, S. R. Sathe

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, Programming Languages

November 16, 2013 by hgpu

The GASPI API specification and its implementation GPI 2.0

D. Grünewald, C. Simmendinger

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Tags: Computer science, Intel Xeon Phi, MPI, Package, Programming Languages

October 9, 2013 by hgpu

UPC on MIC: Early Experiences with Native and Symmetric Modes

M.Luo ,M. Li, A. Venkatesh, X. Lu, D. K. Panda

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Tags: Computer science, Intel Phi, Intel Xeon Phi, Programming Languages

October 9, 2013 by hgpu

Detecting Data Races on OpenCL Kernels with Symbolic Execution

Dino Distefano, Jeremy Dubreil

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Tags: Computer science, OpenCL, Programming Languages

August 15, 2013 by hgpu

Parallel Language Programming In Different Platforms

Pau Vila Fernández

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Tags: Computer science, CUDA, OpenACC, OpenCL, Programming Languages, Thesis

June 21, 2013 by hgpu

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Dominik Grewe, Zheng Wang, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

January 8, 2013 by hgpu

Formal Semantics of Heterogeneous CUDA-C: A Modular Approach with Applications

Chris Hathhorn, Michela Becchi, William L. Harrison, Adam Procter

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Programming Languages

November 28, 2012 by hgpu

Sigma*: Symbolic Learning of Input-Output Specifications

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Programming Languages

November 10, 2012 by hgpu

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

Mads Ruben Burgdorff Kristensen, Simon Andreas Frimann Lund, Troels Blum, Brian Vinter

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Tags: Computer science, OpenCL, Optimization, Package, Programming Languages, Python

November 5, 2012 by hgpu

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Yi Yang, Ping Xiang, Jingfei Kong, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Optimization, Package, Programming Languages

August 27, 2012 by hgpu

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Jungwon Kim, Sangmin Seo, Jun Lee, Jeongho Nah, Gangwon Jo, Jaejin Lee

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Tags: Code generation, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package, Programming Languages, Programming techniques

July 26, 2012 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Exploring GPGPU Acceleration of Process-Oriented Simulations

A Methodology for Translating C-Programs to OpenCL

The GASPI API specification and its implementation GPI 2.0

UPC on MIC: Early Experiences with Native and Symmetric Modes

Detecting Data Races on OpenCL Kernels with Symbolic Execution

Parallel Language Programming In Different Platforms

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Formal Semantics of Heterogeneous CUDA-C: A Modular Approach with Applications

Sigma*: Symbolic Learning of Input-Output Specifications

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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