high performance computing on graphics processing units: hgpu.org

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Toolchain for programming, simulating and studying the XMT many-core architecture

Fuat Keceli, Alexandros Tzannes, George C. Caragea, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, Compilers, Computer science, Hardware Architecture, nVidia, nVidia GeForce GTX 280, Package

December 24, 2011 by hgpu

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Duane Merrill, Andrew Grimshaw

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Sorting

December 24, 2011 by hgpu

Simbuca, using a graphics card to simulate Coulomb interactions in a penning trap

S. Van Gorp, M. Beck, M. Breitenfeldt, V. De Leebeeck, P. Friedag, A. Herlert, T. Iitaka, J. Mader, V. Kozlov, S. Roccia, G. Soti, M. Tandecki, E. Traykov, F. Wauters, Ch. Weinheimer, D. Zakoucky, N. Severijns

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Tags: CUDA, N-body simulation, Nuclear Experiment, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Package, Physics

December 24, 2011 by hgpu

Parallel Inference on Structured Data with CRFs on GPUs

Nico Piatkowski, Katharina Morik

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Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, Package, Tesla C2050

December 21, 2011 by hgpu

Generating SU(Nc) pure gauge lattice QCD configurations on GPUs with CUDA and OpenMP

Nuno Cardoso, Pedro Bicudo

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Package, Physics, QCD

December 21, 2011 by hgpu

Fast Random Graph Generation

Sadegh Heyrani Nobari, Xuesong Lu, Panagiotis Karras, Stephane Bressan

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Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, nVidia GeForce 9800 GT, Package

December 19, 2011 by hgpu

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

Micah Richert, Jayram Moorkanikara Nageswaran, Nikil Dutt, Jeffrey L. Krichmar

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Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C1060

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

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Barbara Chapman, Deepak Eachempati, Oscar Hernandez

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Tags: Code generation, Compilers, Computer science, nVidia, Package, PTX

December 19, 2011 by hgpu

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Tesla C2050

December 18, 2011 by hgpu

Collision for 75-step SHA-1: Intensive Parallelization with GPU

E.A. Grechnikov, A.V. Adinetz

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Tags: Computer science, nVidia, OpenCL, Package, Security, Tesla M2050, Tesla X2070

December 18, 2011 by hgpu

The MOSIX Cluster Operating System for High-Performance Computing on Linux Clusters, Multi-Clusters, GPU Clusters and Clouds

A. Barak, A. Shiloh

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Tags: Cloud, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

December 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

Toolchain for programming, simulating and studying the XMT many-core architecture

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Simbuca, using a graphics card to simulate Coulomb interactions in a penning trap

Parallel Inference on Structured Data with CRFs on GPUs

Generating SU(Nc) pure gauge lattice QCD configurations on GPUs with CUDA and OpenMP

Fast Random Graph Generation

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

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

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Collision for 75-step SHA-1: Intensive Parallelization with GPU

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)