high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

Timothy D. R. Hartley

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5600, Optimization, Performance, Thesis

October 22, 2011 by hgpu

GPU performance prediction using parametrized models

Andreas Resios

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, Optimization, Performance, Thesis

October 22, 2011 by hgpu

Hardware Transactional Memory for GPU Architectures

Wilson W. L. Fung, Inderpreet Singh, Andrew Brownsword, Tor M. Aamodt

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Tags: Bloom filter, Computer science, CUDA, Memory, nVidia, nVidia Quadro FX 5800, OpenCL, Performance, Programming techniques

October 22, 2011 by hgpu

Low-Impact Profiling of Streaming, Heterogeneous Applications

Joseph Marion Lancaster

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Tags: Algorithms, Computer science, Heterogeneous systems, Optimization, Performance, Thesis

October 22, 2011 by hgpu

Concurrent Algorithms and Data Structures for Many-Core Processors

Daniel Cederman

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Performance, Sorting, Thesis

October 21, 2011 by hgpu

Automatic program analysis for data parallel kernels

Calin Juravle

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Programming techniques, Thesis

October 20, 2011 by hgpu

The Potential for a GPU-Like Overlay Architecture for FPGAs

Jeffrey Kingyens, J. Gregory Steffan

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Tags: ATI, ATI CTM, ATI Radeon X1950, Computer science, FPGA, Performance

October 19, 2011 by hgpu

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Pat Hanrahan

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Source codes

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 19, 2011 by hgpu

A Code Transformation Framework for Scientific Applications on Structured Grids

Pei-Hung Lin, Jagan Jayaraj, Paul Woodward, Pen-chung Yew

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Tags: Compilers, Computer science, Fluid dynamics, Optimization, Performance, Programming techniques

October 19, 2011 by hgpu

GPU Parallel Collections For Scala

Kishen Das Kondabagilu Rajanna

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Tags: Compilers, Computer science, CUDA, Java, nVidia, nVidia GeForce 9800 GT, OpenCL, Package, Performance, Thesis

October 19, 2011 by hgpu

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Antonio Wendellde O. Rodrigues, Vincent Aranega, Anne Etien, Frederic Guyomarc'h, Jean-Luc Dekeyser

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Tags: Algorithms, Computer science, nVidia, OpenCL, Performance, Programming techniques, Tesla S1070

October 18, 2011 by hgpu

Evaluating the Performance and Portability of OpenCL

Jarno van der Sanden

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Thesis

October 18, 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

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

GPU performance prediction using parametrized models

Hardware Transactional Memory for GPU Architectures

Low-Impact Profiling of Streaming, Heterogeneous Applications

Concurrent Algorithms and Data Structures for Many-Core Processors

Automatic program analysis for data parallel kernels

The Potential for a GPU-Like Overlay Architecture for FPGAs

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

A Code Transformation Framework for Scientific Applications on Structured Grids

GPU Parallel Collections For Scala

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Evaluating the Performance and Portability of OpenCL

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)