high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

MacroSS: macro-SIMDization of streaming applications

Amir H. Hormati, Yoonseo Choi, Mark Woh, Manjunath Kudlur, Rodric Rabbah, Trevor Mudge, Scott Mahlke

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, Optimization, Performance, Programming Languages

September 7, 2011 by hgpu

CUDA-level performance with python-level productivity for Gaussian mixture model applications

H. Cook, E. Gonina, S. Kamil, G. Friedland, D. Patterson, A. Fox

View

Download (PDF)

Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, OpenCL, Python

September 7, 2011 by hgpu

Chameleon: Virtualizing idle acceleration cores of a heterogeneous multicore processor for caching and prefetching

Dong Hyuk Woo, Joshua B. Fryman, Allan D. Knies, Hsien-Hsin S. Lee

View

Download (PDF)

Tags: Benchmarking, Computer science, Heterogeneous systems, Prefetch

September 7, 2011 by hgpu

Operating systems must support GPU abstractions

Christopher J. Rossbach, Jon Currey, Emmett Witchel

View

Download (PDF)

Tags: Computer science, nVidia, nVidia GeForce GT 230, Operating systems

September 7, 2011 by hgpu

A code-based analytical approach for using separate device coprocessors in computing systems

Volker Hampel, Grigori Goronzy, Erik Maehle

Tags: Computer science, FPGA, Performance

September 7, 2011 by hgpu

GPU-based asynchronous particle swarm optimization

Luca Mussi, Youssef S.G. Nashed, Stefano Cagnoni

Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, Optimization, Performance

September 7, 2011 by hgpu

The future of microprocessors

Shekhar Borkar, Andrew A. Chien

View

Download (PDF)

Tags: Computer science, Energy-efficient computing, Hardware Architecture, Review

September 7, 2011 by hgpu

Energy-efficient mechanisms for managing thread context in throughput processors

Mark Gebhart, Daniel R. Johnson, David Tarjan, Stephen W. Keckler, William J. Dally, Erik Lindholm, Kevin Skadron

View

Download (PDF)

Tags: Computer science, Energy-efficient computing, Hardware Architecture

September 7, 2011 by hgpu

FPGA vs. multi-core CPUs vs. GPUs: hands-on experience with a sorting application

Cristian Grozea, Zorana Bankovic, Pavel Laskov

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia Quadro FX 5600, OpenMP, Sorting

September 7, 2011 by hgpu

Parallel packet classification using GPU co-processors

Alastair Nottingham, Barry Irwin

Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, Security

September 7, 2011 by hgpu

Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators

Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic

View

Download (PDF)

Tags: Benchmarking, Computer science, Hardware Architecture

September 7, 2011 by hgpu

Parallel implementation of conjugate gradient method on graphics processors

Marcin Wozniak, Tomasz Olas, Roman Wyrzykowski

Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Sparse matrix, Tesla C1060

September 7, 2011 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

* * *

high performance computing on graphics processing units: hgpu.org

MacroSS: macro-SIMDization of streaming applications

CUDA-level performance with python-level productivity for Gaussian mixture model applications

Chameleon: Virtualizing idle acceleration cores of a heterogeneous multicore processor for caching and prefetching

Operating systems must support GPU abstractions

A code-based analytical approach for using separate device coprocessors in computing systems

GPU-based asynchronous particle swarm optimization

The future of microprocessors

Energy-efficient mechanisms for managing thread context in throughput processors

FPGA vs. multi-core CPUs vs. GPUs: hands-on experience with a sorting application

Parallel packet classification using GPU co-processors

Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators

Parallel implementation of conjugate gradient method on graphics processors

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

Most viewed papers (last 30 days)