high performance computing on graphics processing units: hgpu.org

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HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon

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Tags: AMD Radeon Instinct MI250X, ATI, Code generation, Computer science, HPC, LLVM, nVidia, nVidia V100, OpenMP, Package

September 6, 2023 by hgpu

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Marc Gonzàlez-Tallada, Enric Morancho

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Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, OpenMP, Task scheduling

August 28, 2023 by hgpu

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

Raúl Nozal, Jose Luis Bosque

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Tags: AMD Radeon RX 5700 XT, ATI, Computer science, Heterogeneous systems, HPC, Molecular dynamics, OpenCL, OpenMP, Package, performance portability

August 28, 2023 by hgpu

Quantifying OpenMP: Statistical Insights into Usage and Adoption

Tal Kadosh, Niranjan Hasabnis, Timothy Mattson, Yuval Pinter, Gal Oren

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Tags: Computer science, CUDA, Databases, Fortran, HPC, MPI, nVidia, OpenACC, OpenCL, OpenMP, Package, SYCL

August 20, 2023 by hgpu

Generating Parallel OpenCL and OpenMP Programs from Dataflow Graphs

Evelyn Borth

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Tags: Benchmarking, Code generation, Computer science, OpenCL, OpenMP, Thesis

August 20, 2023 by hgpu

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Pietro Incardona, Aryaman Gupta, Serhii Yaskovets, Ivo F. Sbalzarini

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, OpenACC, OpenCL, OpenMP, Package, Performance, performance portability, SYCL

July 30, 2023 by hgpu

Creating a Dataset Supporting Translation Between OpenMP Fortran and C++ Code

Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao

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Tags: Computer science, CUDA, Fortran, Machine learning, nVidia, nVidia RTX 6000 Ada, OpenMP, Package

July 24, 2023 by hgpu

Maximizing Parallelism and GPU Utilization For Direct GPU Compilation Through Ensemble Execution

Shilei Tian, Barbara Chapman, Johannes Doerfert

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Tags: Benchmarking, Computer science, CUDA, LLVM, nVidia, nVidia A100, OpenMP, Performance

July 24, 2023 by hgpu

Modeling Parallel Programs using Large Language Models

Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele

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Tags: Code generation, Computer science, HPC, MPI, nVidia, nVidia A100, OpenMP

July 9, 2023 by hgpu

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

William F. Godoy, Pedro Valero-Lara, Keita Teranishi, Prasanna Balaprakash, Jeffrey S. Vetter

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Tags: AI, Artificial intelligence, Benchmarking, Code generation, Computer science, CUDA, Fortran, HPC, Julia, nVidia, OpenACC, OpenMP, Package, Python

July 2, 2023 by hgpu

GPU First – Execution of Legacy CPU Codes on GPUs

Shilei Tian, Tom Scogland, Barbara Chapman, Johannes Doerfert

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenMP

June 25, 2023 by hgpu

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña

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Tags: Algorithms, Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla A100

June 25, 2023 by hgpu

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

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

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

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

Anatomizing Deep Learning Inference in Web Browsers

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high performance computing on graphics processing units: hgpu.org

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

Quantifying OpenMP: Statistical Insights into Usage and Adoption

Generating Parallel OpenCL and OpenMP Programs from Dataflow Graphs

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Creating a Dataset Supporting Translation Between OpenMP Fortran and C++ Code

Maximizing Parallelism and GPU Utilization For Direct GPU Compilation Through Ensemble Execution

Modeling Parallel Programs using Large Language Models

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

GPU First – Execution of Legacy CPU Codes on GPUs

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Recent source codes

GPU-Smash: Compression abstraction library

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

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

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

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