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Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

David Beniamine

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Tags: Computer science, CUDA, nVidia, nVidia Quadro NVS 300, Task scheduling, Tesla C2050, Thesis

January 29, 2014 by hgpu

Scheduling on Manycore and Heterogeneous Graphics Processors

Stanley Tzeng

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Thesis

January 28, 2014 by hgpu

Automatic Resource-Constrained Static Task Parallelization

Dounia Khaldi

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Tags: Algorithms, Code generation, Computer science, MPI, OpenCL, Task scheduling, Thesis

January 28, 2014 by hgpu

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Bo Fang, Karthik Pattabiraman, Matei Ripeanu, Sudhanva Gurumurthi

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

January 28, 2014 by hgpu

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

Vineeth Thamarassery Mekkat

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce 8600 GTS, Thesis

January 28, 2014 by hgpu

Autotuning Programs with Algorithmic Choice

Jason Ansel

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Tags: Algorithms, ATI, ATI Radeon HD 6630 M, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2070, Thesis

January 28, 2014 by hgpu

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Jason Power, Joel Hestness, Marc S. Orr, Mark D. Hill, David A. Wood

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Tags: Computer science, CUDA, GPGPU-sim, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

January 26, 2014 by hgpu

A Dynamic Offload Scheduler for spatial multitasking on Intel Xeon Phi Coprocessor

Takamichi Miyamoto, Kazuhisa Ishizaka, Takeo Hosomi

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Tags: Computer science, Intel Xeon Phi, Task scheduling

January 26, 2014 by hgpu

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Marcel Koster, Roland Leissa, and Sebastian Hack, Richard Membarth, Philipp Slusallek

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

January 26, 2014 by hgpu

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Anatoly V. Panyukov, Valentin A. Golodov

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, nVidia GeForce GTX 460

January 26, 2014 by hgpu

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Naoya Maruyama, Takayuki Aoki

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla K20, Tesla M2075

January 26, 2014 by hgpu

Hybrid strategy for stencil computations on the APU

Pacome Eberhart, Issam Said, Pierre Fortin

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Tags: AMD, APU, Computer science, Numerical Analysis, OpenCL, Partial differential equations

January 26, 2014 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

Scheduling on Manycore and Heterogeneous Graphics Processors

Automatic Resource-Constrained Static Task Parallelization

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications

Performance-Correctness Challenges in Emerging Heterogeneous Multicore Processors

Autotuning Programs with Algorithmic Choice

gem5-gpu: A Heterogeneous CPU-GPU Simulator

A Dynamic Offload Scheduler for spatial multitasking on Intel Xeon Phi Coprocessor

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Computing Best Possible Pseudo-Solutions to Interval Linear Systems of Equations

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Hybrid strategy for stencil computations on the APU

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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