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MetaCL – A Model-Based Approach to Programming Heterogeneous Architectures Using OpenCL

William Spencer Crosswy

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Numerical Analysis, OpenCL, Thesis

April 18, 2012 by hgpu

Heterogeneous Highly Parallel Implementation of Matrix Exponentiation Using GPU

Chittampally Vasanth Raja, Srinivas Balasubramanian, Prakash S. Raghavendra

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Tags: Computer science, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, OpenCL, Tesla C2050

April 16, 2012 by hgpu

A Scalable Framework for Heterogeneous GPU-Based Clusters

Fengguang Song, Jack Dongarra, Stanimire Tomov

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Tags: Algorithms, Computer science, CUDA, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, Tesla M2070

April 7, 2012 by hgpu

OpenCL framework for a CPU, GPU, and FPGA Platform

Taneem Ahmed

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Tags: ATI, ATI Radeon HD 5450, Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

April 6, 2012 by hgpu

Enhancing Performance of Simulations using GPGPU

Shadi Alawneh, Dennis Peters

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia

April 5, 2012 by hgpu

Towards Adaptive GPU Resource Management for Embedded Real-Time Systems

Junsung Kim, Raj Rajkumar, Shinpei Kato

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia

April 2, 2012 by hgpu

GPU Programming Strategies and Trends in GPU Computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Optimization, Overview

April 2, 2012 by hgpu

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

March 28, 2012 by hgpu

Dynamic Translation of Runtime Environments for Heterogeneous Computing

Rodrigo Dominguez

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Thesis

March 27, 2012 by hgpu

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Shivani Raghav, Christian Pinto, Martino Ruggiero, Andrea Marongiu, David Atienza, Luca Benini

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Operating systems, Software Engineering, Tesla C2070

March 26, 2012 by hgpu

Impact of asynchronism on GPU accelerated parallel iterative computations

Sylvain Contassot-Vivier, Thomas Jost, Stephane Vialle

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Partial differential equations, PDEs, Performance

March 22, 2012 by hgpu

Hierarchical N-body simulations with auto-tuning for heterogeneous systems

Rio Yokota, Lorena A. Barba

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Tags: Algorithms, CUDA, Heterogeneous systems, Mathematical Software, N-body simulation, Numerical Analysis, nVidia, nVidia GeForce GTX 590, Physics, Tesla C2050

March 22, 2012 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

MetaCL – A Model-Based Approach to Programming Heterogeneous Architectures Using OpenCL

Heterogeneous Highly Parallel Implementation of Matrix Exponentiation Using GPU

A Scalable Framework for Heterogeneous GPU-Based Clusters

OpenCL framework for a CPU, GPU, and FPGA Platform

Enhancing Performance of Simulations using GPGPU

Towards Adaptive GPU Resource Management for Embedded Real-Time Systems

GPU Programming Strategies and Trends in GPU Computing

Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems

Dynamic Translation of Runtime Environments for Heterogeneous Computing

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Impact of asynchronism on GPU accelerated parallel iterative computations

Hierarchical N-body simulations with auto-tuning for heterogeneous systems

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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