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Efficient Synchronization Primitives for GPUs

Jeff A. Stuart, John D. Owens

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Operating systems

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

Enabling Computational Dynamics in Distributed Computing Environments Using a Heterogeneous Computing Template

Dan Negrut, Toby Heyn, Andrew Seidl, Dan Melanz, David Gorsich, David Lamb

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Tags: Collision detection, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Tesla C1060, Visualization

October 20, 2011 by hgpu

A high performance computing framework for physics-based modeling and simulation of military ground vehicles

Dan Negrut, David Lamb, David Gorsich

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Tags: Algorithms, Collision detection, CUDA, Distributed computing, Heterogeneous systems, nVidia, Physics, Tesla C1060

October 20, 2011 by hgpu

Experimental B+-tree for GPU

Krzysztof Kaczmarski

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 280, Sorting

October 20, 2011 by hgpu

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

Ana Balevic, Bart Kienhuis

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Programming techniques, Tesla C2050

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

Heterogeneous Accelerated Bioinformatics-Perspectives for Cancer Research

Eric A. Stahlberg, T. Steinke, M. C. Smith, S. Chandrasekaran, B. Chapman

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, Medicine, nVidia, OpenCL, Review

October 19, 2011 by hgpu

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

Simon McIntosh-Smith

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

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

Characterization of FPGA-based High Performance Computers

Karl Savio Pimenta Pereira

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Tags: Algorithms, Benchmarking, Chemistry, Computer science, CUDA, DSP, FFT, FPGA, Molecular dynamics, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Thesis

October 18, 2011 by hgpu

Design and Performance of the OP2 Library for Unstructured Mesh Applications

Carlo Bertolli, Adam Betts, Gihan Mudalige, Mike Giles, Paul Kelly

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Source codes

Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, OpenMP, Package, Tesla C2050

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

Efficient Synchronization Primitives for GPUs

Automatic program analysis for data parallel kernels

Enabling Computational Dynamics in Distributed Computing Environments Using a Heterogeneous Computing Template

A high performance computing framework for physics-based modeling and simulation of military ground vehicles

Experimental B+-tree for GPU

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

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

Heterogeneous Accelerated Bioinformatics-Perspectives for Cancer Research

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

GPU Parallel Collections For Scala

Characterization of FPGA-based High Performance Computers

Design and Performance of the OP2 Library for Unstructured Mesh Applications

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

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