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Optimizing OpenCL Local Work Group Size With Machine Learning

Markus Schlafli

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Tags: ATI, ATI Radeon HD 7850, Computer science, Machine learning, OpenCL, Performance, PTX

August 18, 2015 by hgpu

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

Saeed Taheri, Apan Qasem, Martin Burtscher

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Performance, Tesla K20

August 14, 2015 by hgpu

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Siyi Huang, Rainer Spurzem, Peter Berczik

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Tags: Astrophysics, CUDA, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Performance, Tesla M2050, Tesla M2070

August 12, 2015 by hgpu

Optimized Event-Driven Runtime Systems for Programmability and Performance

Sagnak Tasrlar

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Tags: Computer science, Intel Xeon Phi, OpenMP, Performance, Thesis

August 3, 2015 by hgpu

Processing Large-scale XML Files on GPGPU Cluster

Ping Liu

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenMPI, Performance, Tesla M2075

July 27, 2015 by hgpu

Parallel Programming in Actor-Based Applications via OpenCL

Paul Harvey, Kristian Hentschel, Joseph Sventek

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Tags: AMD Radeon R9 290X, ATI, Computer science, OpenACC, OpenCL, Package, Performance

July 20, 2015 by hgpu

Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

Mei Wen, Da-fei Huang, Chang-qing Xun, Dong Chen

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Performance

July 20, 2015 by hgpu

Adaptive parallelism mapping in dynamic environments using machine learning

Murali Krishna Emani

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Tags: Computer science, Machine learning, OpenMP, Performance, Thesis

July 15, 2015 by hgpu

Evaluating the capabilities of the Xeon Phi platform in the context of software-only, thread-level speculation

Alvaro Estebanez, Diego R. Llanos, Arturo Gonzalez-Escribano

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

July 13, 2015 by hgpu

Characterizing and Optimizing Irregular Applications on Graphics Processing Units

Tao Zhang

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance, Thesis

July 10, 2015 by hgpu

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Alexey Lastovetsky, Lukasz Szustak, Roman Wyrzykowski

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Tags: Computer science, Intel Xeon Phi, Performance

July 8, 2015 by hgpu

Autotuning OpenACC Work Distribution via Direct Search

Calvin Montgomery, Jeffrey L. Overbey, Xuechao Li

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Tags: Computer science, MPI, nVidia, OpenACC, Package, Performance, Python, Tesla K20

July 8, 2015 by hgpu

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

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high performance computing on graphics processing units: hgpu.org

Optimizing OpenCL Local Work Group Size With Machine Learning

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Optimized Event-Driven Runtime Systems for Programmability and Performance

Processing Large-scale XML Files on GPGPU Cluster

Parallel Programming in Actor-Based Applications via OpenCL

Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

Adaptive parallelism mapping in dynamic environments using machine learning

Evaluating the capabilities of the Xeon Phi platform in the context of software-only, thread-level speculation

Characterizing and Optimizing Irregular Applications on Graphics Processing Units

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Autotuning OpenACC Work Distribution via Direct Search

Recent source codes

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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