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Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

D.P. Playne, K.A. Hawick

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Tags: Code generation, Computer science, CUDA, Field equations, nVidia, nVidia GeForce GTX 580

May 25, 2013 by hgpu

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 480

May 25, 2013 by hgpu

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K. A. Hawick, D. P. Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

GEMTC: GPU Enabled Many-Task Computing

Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Performance

May 25, 2013 by hgpu

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

A.-E Hugo A. Guermouche P.-A. Wacrenier R. Namyst

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla M2070

May 23, 2013 by hgpu

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Derek R. Hower, Bradford M. Beckmann, Benedict R. Gaster, Blake A. Hechtman, Mark D. Hill, Steven K. Reinhardt, David A. Wood

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance

May 23, 2013 by hgpu

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Salvatore Cuomo, Ardelio Gallettiy, Giulio Giuntay, Alfredo Staracey

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla C1060

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

An Investigation of the Performance Portability of OpenCL

S.J. Pennycook, S.D. Hammond, S.A. Wright, J.A. Herdman, I. Miller, S.A. Jarvis

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Source codes

Tags: ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, Fortran, MPI, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

May 21, 2013 by hgpu

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture

Lukasz Swierczewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTS 250, Security, Tesla C2050

May 21, 2013 by hgpu

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

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high performance computing on graphics processing units: hgpu.org

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

OpenCL Performance Evaluation on Modern Multi Core CPUs

GEMTC: GPU Enabled Many-Task Computing

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

An Investigation of the Performance Portability of OpenCL

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture

Recent source codes

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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