high performance computing on graphics processing units: hgpu.org

Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston

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Tags: CUDA, Deep learning, Earth and Space Sciences, Neural networks, nVidia, TensorFlow, Tesla V100, Weather prediction

October 6, 2018 by hgpu

HSTREAM: A directive-based language extension for heterogeneous stream computing

Suejb Memeti, Sabri Pllana

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Quadro P 4000, OpenMP

October 6, 2018 by hgpu

Parallel LZ77 Decoding using a GPU

Emmanuel Morfiadakis

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 840 M, Thesis

September 23, 2018 by hgpu

Support for Parallel Scan in OpenMP

Eder Maicol Gomez Zegarra

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, OpenCL, OpenMP, Sorting, Thesis

September 23, 2018 by hgpu

SoaAlloc: Accelerating Single-Method Multiple-Objects Applications on GPUs

Matthias Springer

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Programming Languages

September 23, 2018 by hgpu

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs

Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

A Comparative Measurement Study of Deep Learning as a Service Framework

The Ocean Tensor Package

Towards Efficient Large-Scale Graph Neural Network Computing

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Exascale Deep Learning for Climate Analytics

HSTREAM: A directive-based language extension for heterogeneous stream computing

Parallel LZ77 Decoding using a GPU

Support for Parallel Scan in OpenMP

SoaAlloc: Accelerating Single-Method Multiple-Objects Applications on GPUs

Recent source codes

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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