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MapReduce for Counting Word Frequencies with MPI and GPUs

Nithin Kavi

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Tags: Algorithms, Computer science, CUDA, Julia, MapReduce, MPI, NLP, nVidia, Optimization, Package, Tesla V100

June 19, 2022 by hgpu

CuPBoP: CUDA for Parallelized and Broad-range Processors

Ruobing Han, Jun Chen, Bhanu Garg, Jeffrey Young, Jaewoong Sim, Hyesoon Kim

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia GeForce GTX 1660 Ti, OpenMP

June 19, 2022 by hgpu

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

John Keith Holmen

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX Titan X, performance portability, Task scheduling

June 5, 2022 by hgpu

The Celerity High-level API: C++20 for Accelerator Clusters

Peter Thoman, Florian Tischler, Philip Salzmann, Thomas Fahringer

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Tags: Code generation, Computer science, Data parallelism, MPI, nVidia, nVidia GeForce RTX 2070, Package, Programming techniques, SYCL

May 1, 2022 by hgpu

Machine Learning for CUDA+MPI Design Rules

Carl Pearson, Aurya Javeed, Karen Devine

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Tags: Computer science, CUDA, Machine learning, Monte Carlo simulation, MPI, nVidia, nVidia A100

March 20, 2022 by hgpu

HipBone: A performance-portable GPU-accelerated C++ version of the NekBone benchmark

Noel Chalmers, Abhishek Mishra, Damon McDougall, Tim Warburton

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Benchmarking, Computer science, CUDA, HIP, HPC, MPI, nVidia, Package, Performance, Tesla V100

March 11, 2022 by hgpu

Integrating SkePU’s algorithmic skeletons with GPI on a cluster

Joel Almqvist

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Tags: Computer science, CUDA, Distributed computing, HPC, MPI, nVidia, OpenCL, OpenMP, Thesis

March 6, 2022 by hgpu

Performance Evaluation of Python ParallelProgramming Models: Charm4Py and mpi4py

Zane Fink, Simeng Liu, Jaemin Choi, Matthias Diener, Laxmikant V. Kale

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Tags: Benchmarking, Computer science, CUDA, Distributed computing, HPC, Machine learning, MPI, nVidia, Package, Performance, Python, Tesla V100

November 14, 2021 by hgpu

Monitoring Collective Communication Among GPUs

Muhammet Abdullah Soyturk, Palwisha Akhtar, Erhan Tezcan, Didem Unat

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Tags: Computer science, CUDA, MPI, nVidia, Package, Performance, Tesla V100

October 24, 2021 by hgpu

OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems

Nawras Alnaasan, Arpan Jain, Aamir Shafi, Hari Subramoni, Dhabaleswar K Panda

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Tags: Benchmarking, Computer science, CUDA, Deep learning, HPC, Machine learning, MPI, nVidia, Python, Tesla V100

October 24, 2021 by hgpu

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

Ludwig Kratzl

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Intel, Intel UHD 630, MPI, nVidia, nVidia GeForce RTX 3090, OpenCL, Package, performance portability, SYCL, Thesis

August 29, 2021 by hgpu

EXA2PRO: A Framework for High Development Productivity on Heterogeneous Computing Systems

Lazaros Papadopoulos, Dimitris John Soudris, Christoph Kessler, August Ernstsson, Johan Ahlqvist, Nikos Vasilas, Athanasios Papadopoulos, Panos Seferlis, Charles Prouveur, Matthieu Haefele, Samuel Paul Thibault, Athanasios Salamanis, Theodoros Ioakimidis, Dionisis D. Kehagias

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, MPI, nVidia, nVidia Quadro P 620, OpenCL, OpenMP, Tesla P100, Tesla V100

August 22, 2021 by hgpu

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

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