high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

Bo Duan, Wendi Wang, Xingjian Li, Chunming Zhang, Peiheng Zhang, Ninghui Sun

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Tags: Algorithms, Computer science, CUDA, FFT, FPGA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 20, 2011 by hgpu

3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

Jason Cong, Muhuan Huang, Yi Zou

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Tags: CUDA, FPGA, Image processing, nVidia, Optimization, Tesla C1060

December 19, 2011 by hgpu

Optimization of mapped functions sequences using fusions on GPU

Jan Fousek

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, Optimization, Thesis

December 19, 2011 by hgpu

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Dounia Khaldi, Corinne Ancourt, Francois Irigoin

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Tags: Benchmarking, Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, MPI, nVidia, OpenMP, Optimization, Package

December 19, 2011 by hgpu

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Petr Pospichal, Eoin Murphy, Michael O'Neill, Josef Schwarz, Jiri Jaros

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Genetic programming, Java, nVidia, nVidia GeForce GTX 480, Optimization

December 19, 2011 by hgpu

Parallel paradigms in optimal structural design

Van Huyssteen, Salomon Stephanus

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Thesis

December 18, 2011 by hgpu

Massively Parallel Logic Simulation with GPUs

Yuhao Zhu, Bo Wang, Yangdong Deng

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce GTX 280, Optimization, Performance

December 17, 2011 by hgpu

Extendable pattern-oriented optimization directives

Huimin Cui, Jingling Xue, Lei Wang, Yang Yang, Xiaobing Feng, Dongrui Fan

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization

December 17, 2011 by hgpu

Code Optimization Techniques for Graphics Processing Units

Fernando Magno Quintao Pereira

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Tags: Algorithms, Book, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, Optimization, Package, Programming techniques, PTX, Tutorial

December 17, 2011 by hgpu

A Parallel GPU Version of the Traveling Salesman Problem

Molly A. O'Neil, Dan Tamir, Martin Burtscher

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Package, Tesla C2050

December 16, 2011 by hgpu

Efficient XML Path Filtering Using GPUs

Roger Moussalli, Robert Halstead, Mariam Salloum, Walid Najjar, Vassilis J. Tsotras

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Tags: Computer science, CUDA, Data Structures and Algorithms, FPGA, nVidia, Optimization, Tesla C1060

December 16, 2011 by hgpu

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

Uzi Vishkin, Rajeev Barua

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Tags: Algorithms, Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Prefetch, Rendering, Thesis

December 16, 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

Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

Optimization of mapped functions sequences using fusions on GPU

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Parallel paradigms in optimal structural design

Massively Parallel Logic Simulation with GPUs

Extendable pattern-oriented optimization directives

Code Optimization Techniques for Graphics Processing Units

A Parallel GPU Version of the Traveling Salesman Problem

Efficient XML Path Filtering Using GPUs

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

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)