high performance computing on graphics processing units: hgpu.org

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dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures

Steven Eliuk, Cameron Upright, Anthony Skjellum

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Linear Algebra, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, OpenMPI, Tesla K80

April 9, 2016 by hgpu

An Exploratory Study of High Performance Graphics Application Programming Interfaces

Joseph Shiraef

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Tags: AMD Radeon R9 290X, ATI, Computer science, DirectX, nVidia, nVidia GeForce GTX 970, OpenGL, Performance, Thesis, Vulkan

April 6, 2016 by hgpu

gpucc: an open-source GPGPU compiler

Jingyue Wu, Artem Belevich, Eli Bendersky, Mark Heffernan, Chris Leary, Jacques Pienaar, Bjarke Roune, Rob Springer, Xuetian Weng, Robert Hundt

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Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, Presentation, Tesla K40

April 6, 2016 by hgpu

Automatic test case reduction of randomly generated OpenCL kernels

Moritz Pflanzer

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Tags: Code generation, Computer science, LLVM, nVidia, nVidia GeForce GT 630, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, nVidia Quadro K5200, OpenCL, Thesis

April 6, 2016 by hgpu

Are Very Deep Neural Networks Feasible on Mobile Devices?

S. Rallapalli, H. Qiu, A. J. Bency, S. Karthikeyan, R. Govindan, B.S.Manjunath, R. Urgaonkar

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson TK1

April 6, 2016 by hgpu

GPU-accelerated stochastic predictive control of drinking water networks

Ajay K. Sampathirao, Pantelis Sopasakis, Alberto Bemporad, Panagiotis Patrinos

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Tags: CUDA, Mathematics, nVidia, Tesla C2075

April 6, 2016 by hgpu

Implementation of the SYCL Heterogeneous Computing Library

Peter Zuzek

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Tags: Code generation, Computer science, Heterogeneous systems, OpenCL, Package, SYCL, Thesis

April 3, 2016 by hgpu

Classiffication-based Financial Markets Prediction using Deep Neural Networks

Matthew Dixon, Diego Klabjan, Jin Hoon Bang

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Tags: Computer science, Deep learning, Finance, Intel Xeon Phi, Neural networks

April 3, 2016 by hgpu

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Kenichi W. Okamoto, Priyanga Amarasekare

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Tags: Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 690, Package

April 3, 2016 by hgpu

Dynamic Sparse-Matrix Allocation on GPUs

James King, Thomas Gilray, Robert M. Kirby, Matthew Might

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Tags: Benchmarking, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse matrix, Tesla K20

April 3, 2016 by hgpu

Evaluating the Performance Impact of Multiple Streams on the MIC-based Heterogeneous Platform

Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Cheng Chen, Canqun Yang

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

April 3, 2016 by hgpu

A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs

Guixia He, Jiaquan Gao

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla C2050

March 29, 2016 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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high performance computing on graphics processing units: hgpu.org

Applications

dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures

An Exploratory Study of High Performance Graphics Application Programming Interfaces

gpucc: an open-source GPGPU compiler

Automatic test case reduction of randomly generated OpenCL kernels

Are Very Deep Neural Networks Feasible on Mobile Devices?

GPU-accelerated stochastic predictive control of drinking water networks

Implementation of the SYCL Heterogeneous Computing Library

Classiffication-based Financial Markets Prediction using Deep Neural Networks

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Dynamic Sparse-Matrix Allocation on GPUs

Evaluating the Performance Impact of Multiple Streams on the MIC-based Heterogeneous Platform

A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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