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A Study of Mixed Precision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, performance portability, Tesla V100

September 19, 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

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Konstantin Herb, Pol Welter

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Tags: BLAS, Computational Physics, Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla V100

August 22, 2021 by hgpu

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

Shandong Lao, Aaron Holt, Deepthi Vaidhynathan, Hariswaran Sitaraman, Christine M. Hrenya, Thomas Hauser

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Tags: cfd, CUDA, Fluid dynamics, HPC, nVidia, nVidia A100, Tesla V100

August 22, 2021 by hgpu

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Fabian Knorr, Peter Thoman, Thomas Fahringer

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, Package, SYCL, Tesla V100

August 8, 2021 by hgpu

Performance assessment of CUDA and OpenACC in large scale combustion simulations

Guillermo Oyarzun, Daniel Mira, Guillaume Houzeaux

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Tags: CUDA, nVidia, OpenACC, Performance, Physics, Tesla V100

August 8, 2021 by hgpu

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Jan Solanti, Michal Babej, Julius Ikkala, Vinod Kumar Malamal Vadakital, Pekka Jääskeläinen

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Tags: Computer science, GPU cluster, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 2080 Ti, OpenCL, Package, Rendering, Tesla P100, Tesla V100

August 8, 2021 by hgpu

Effective GPU Sharing Under Compiler Guidance

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, LLVM, Neural networks, nVidia, Tesla P100, Tesla V100

July 25, 2021 by hgpu

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Package, Tesla V100

July 11, 2021 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

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Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

A Sorting Library for FPGA Implementation in OpenCL Programming

Ryohei Kobayashi, Kento Miura, Norihisa Fujita, Taisuke Boku, Toshiyuki Amagasa

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Tags: Algorithms, Computer science, FPGA, nVidia, OpenCL, Sorting, Tesla V100

July 4, 2021 by hgpu

Productivity, Portability, Performance: Data-Centric Python

Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler

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Tags: Computer science, FPGA, HPC, nVidia, Python, Tesla V100

July 4, 2021 by hgpu

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high performance computing on graphics processing units: hgpu.org

A Study of Mixed Precision Strategies for GMRES on GPUs

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

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Performance assessment of CUDA and OpenACC in large scale combustion simulations

PoCL-R: A Scalable Low Latency Distributed OpenCL Runtime

Effective GPU Sharing Under Compiler Guidance

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Opening the Black Box: Performance Estimation during Code Generation for GPUs

A Sorting Library for FPGA Implementation in OpenCL Programming

Productivity, Portability, Performance: Data-Centric Python

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