high performance computing on graphics processing units: hgpu.org

Georgios Smaragdos, Georgios Chatzikonstantis, Rahul Kukreja, Harrys Sidiropoulos, Dimitrios Rodopoulos, Ioannis Sourdis, Zaid Al-Ars, Christoforos Kachris, Dimitrios Soudris, Chris I. De Zeeuw, Christos Strydis

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Tags: Biophysics, Computer science, Heterogeneous systems, Intel Xeon Phi, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan X, OpenMP

December 10, 2016 by hgpu

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Florencio Balboa Usabiaga, Blaise Delmotte, Aleksandar Donev

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Tags: Condensed matter, CUDA, nVidia, Package, Physics, pyCUDA, Soft Condensed Matter

December 6, 2016 by hgpu

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

Mark Govett, Jim Rosinski, Jacques Middlecoff, Tom Henderson, Jin Lee, Alexander MacDonald, Paul Madden, Julie Schramm, Antonio Duarte

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Tags: CUDA, Earth and Space Sciences, Fortran, Intel Xeon Phi, nVidia, OpenACC, Tesla K80, Weather prediction, Weather Prediction Model

December 6, 2016 by hgpu

GPU-accelerated algorithms for many-particle continuous-time quantum walks

Enrico Piccinini, Claudia Benedetti, Ilaria Siloi, Matteo G. A. Paris, Paolo Bordone

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Tags: Algorithms, Benchmarking, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 980, OpenMP, Physics, Quantum computing, Quantum Physics, Quantum walks, Tesla K40, Tesla K80, Tesla M2050

December 6, 2016 by hgpu

A Comparison of GPU Execution Time Prediction using Machine Learning and Analytical Modeling

Marcos Amaris, Raphael Y. de Camargo, Mohamed Dyab, Alfredo Goldman, Denis Trystram

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Tags: Analytical model, Benchmarking, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 970, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X, nVidia Quadro K5200, Package, Performance, Tesla K20, Tesla K40

December 6, 2016 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

nmfgpu4R: GPU-Accelerated Computation of the Non-Negative Matrix Factorization (NMF) Using CUDA Capable Hardware

GaDei: On Scale-up Training As A Service For Deep Learning

cusFFT: A High-Performance Sparse Fast Fourier Transform Algorithm on GPUs

GPGPU Accelerated Deep Object Classification on a Heterogeneous Mobile Platform

Implementing and Evaluating Candidate-Based Invariant Generation

Performance Evaluation and Optimization of HPCG benchmark on CPU + MIC platform

Adaptive Work-Efficient Connected Components on the GPU

BrainFrame: A heterogeneous accelerator platform for neuron simulations

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

GPU-accelerated algorithms for many-particle continuous-time quantum walks

A Comparison of GPU Execution Time Prediction using Machine Learning and Analytical Modeling

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)