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Designing a Unified Programming Model for Heterogeneous Machines

Michael Garland, Manjunath Kudlur, Yili Zheng

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2050, Tesla X2090

August 26, 2012 by hgpu

Improving OpenACC compatibility within accULL

Ivan Lopez-Rodriguez

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenACC, OpenCL, Tesla C2050

August 22, 2012 by hgpu

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Chunsheng Feng, Shi Shu, Jinchao Xu, Chen-Song Zhang

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Tags: Computational Physics, CUDA, Differential equations, FFT, Heterogeneous systems, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Partial differential equations, PDEs, Poisson equation

August 22, 2012 by hgpu

Dense Matrix Computation on a Heterogenous Architecture: A Block Synchronous Approach

Kyungjoo Kim, Victor Eijkhout, Robert A. van de Geijn

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Tags: Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Package, Tesla M2070, Tesla S1070

August 13, 2012 by hgpu

OP2: An Active Library Framework for Solving Unstructured Mesh-based Applications on Multi-Core and Many-Core Architectures

G.R. Mudalige, M.B. Giles, I. Reguly, C. Bertolli, P.H.J Kelly

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, Performance, Tesla C2050, Tesla C2070

August 11, 2012 by hgpu

Kargus: a Highly-scalable Software-based Intrusion Detection System

Muhammad Jamshed, Jihyung Lee, Sangwoo Moon, Insu Yun, Deokjin Kim, Sungryoul Lee, Yung Yi, KyoungSoo Park

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Security

August 9, 2012 by hgpu

Coordinated system level resource management for heterogeneous many-core platforms

Vishakha Gupta

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX, Thesis

August 6, 2012 by hgpu

Power Management for GPU-CPU Heterogeneous Systems

Xue Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, Thesis

August 3, 2012 by hgpu

Interference-driven resource management for GPU-based heterogeneous clusters

Rajat Phull, Cheng-Hong Li, Kunal Rao, Srihari Cadambi, Srimat Chakradhar

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, PC cluster, Performance, Tesla C2050

August 1, 2012 by hgpu

accULL: An User-directed Approach to Heterogeneous Programming

Ruyman Reyes, Ivan Lopez, Juan J. Fumero, Francisco de Sande

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Python, Tesla C1060, Tesla C2050

July 31, 2012 by hgpu

A virtual memory based runtime to support multi-tenancy in clusters with GPUs

Michela Becchi, Kittisak Sajjapongse, Ian Graves, Adam Procter, Vignesh Ravi, Srimat Chakradhar

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, PC cluster, Tesla C1060, Tesla C2050, Virtualization

July 27, 2012 by hgpu

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Jungwon Kim, Sangmin Seo, Jun Lee, Jeongho Nah, Gangwon Jo, Jaejin Lee

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Tags: Code generation, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package, Programming Languages, Programming techniques

July 26, 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

Designing a Unified Programming Model for Heterogeneous Machines

Improving OpenACC compatibility within accULL

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Dense Matrix Computation on a Heterogenous Architecture: A Block Synchronous Approach

OP2: An Active Library Framework for Solving Unstructured Mesh-based Applications on Multi-Core and Many-Core Architectures

Kargus: a Highly-scalable Software-based Intrusion Detection System

Coordinated system level resource management for heterogeneous many-core platforms

Power Management for GPU-CPU Heterogeneous Systems

Interference-driven resource management for GPU-based heterogeneous clusters

accULL: An User-directed Approach to Heterogeneous Programming

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

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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