high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Source-to-source transformations for irregular and multithreaded code optimization

Julien Jaeger

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, Thesis

July 24, 2012 by hgpu

LBCL: multi-device automatic load balancing

Carlos S. de la Lama, Pablo Toharia, Oscar D. Robles, Jose Luis Bosque

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Tags: Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

July 23, 2012 by hgpu

Scaling CUDA for Distributed Heterogeneous Processors

Siu Kwan Lam

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, Package, PTX, Python, Thesis

July 20, 2012 by hgpu

GPU-Accelerated Point-Based Color Bleeding

Ryan Daniel Schmitt

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Tags: Algorithms, ATI, ATI Radeon HD 5970, Computer science, Heterogeneous systems, OpenGL, Rasterization, Thesis

July 20, 2012 by hgpu

Optimizing MapReduce for GPUs with effective shared memory usage

Linchuan Chen, Gagan Agrawal

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Tags: Computer science, Heterogeneous systems, MapReduce, Memory, nVidia, nVidia Quadro FX 5800, Performance

July 16, 2012 by hgpu

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Abdullah Gharaibeh, Lauro Beltrao Costa, Elizeu Santos-Neto, Matei Ripeanu

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Tags: Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, Optimization, Performance, Programming Languages, Programming techniques, Tesla C2050

July 16, 2012 by hgpu

Distributed OpenCL: a platform for distributed, heterogeneous computing for domain scientists

William H. Dillon (William Hall)

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Tags: ATI, ATI Radeon HD 4870, Computer science, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, OpenCL

July 16, 2012 by hgpu

Data Partitioning on Heterogeneous Multicore and Multi-GPU Systems Using Functional Performance Models of Data-Parallel Applications

Ziming Zhong, Vladimir Rychkov, Alexey Lastovetsky

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 680, Tesla C870

July 12, 2012 by hgpu

Invitation to a Standard Programming Interface for Massively Parallel Computing Environment: OpenCL

Shinichi Yamagiwa

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro NVS 4200 M, OpenCL, Overview, Programming techniques, Tutorial

July 11, 2012 by hgpu

Runtime Systems and Scheduling Support for High-End CPU-GPU Architectures

Vignesh Trichy Ravi

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

July 10, 2012 by hgpu

A Generic Library for Stencil Computations

Mauro Bianco, Ugo Varetto

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Mathematical Software, MPI, nVidia, PC cluster, Performance, Tesla M2090

July 10, 2012 by hgpu

High Performance System in GPU and CUDA Media Processing System

M.Chithik Raja

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Tags: Computer science, CUDA, Heterogeneous systems, HLSL, nVidia, nVidia GeForce 6600 GT, nVidia GeForce 8800 GTX, nVidia GeForce 8800 Ultra

July 6, 2012 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

Source-to-source transformations for irregular and multithreaded code optimization

LBCL: multi-device automatic load balancing

Scaling CUDA for Distributed Heterogeneous Processors

GPU-Accelerated Point-Based Color Bleeding

Optimizing MapReduce for GPUs with effective shared memory usage

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Distributed OpenCL: a platform for distributed, heterogeneous computing for domain scientists

Data Partitioning on Heterogeneous Multicore and Multi-GPU Systems Using Functional Performance Models of Data-Parallel Applications

Invitation to a Standard Programming Interface for Massively Parallel Computing Environment: OpenCL

A Generic Library for Stencil Computations

High Performance System in GPU and CUDA Media Processing System

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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