high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

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

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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

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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

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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

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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

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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

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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

Compiler-directed memory management for heterogeneous MPSoCs

Miao Wang, Francois Bodin

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Tags: Cell processor, Computer science, Heterogeneous systems, Memory, Memory model, Optimization

September 7, 2011 by hgpu

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

V. Aggarwal, A. George, K. Yalamanchili, C. Yoon, H. Lam, G. Stitt

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Tags: Computer science, FPGA, Heterogeneous systems, Performance, Programming Languages, Programming techniques

September 6, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

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

Compiler-directed memory management for heterogeneous MPSoCs

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)