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GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation

Jhe-Yu Liou, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Deep learning, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia P100

October 29, 2023 by hgpu

Performance/power assessment of CNN packages on embedded automotive platforms

Paolo Burgio, Gianluca Brilli

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Tags: CNN, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX2, Performance

October 22, 2023 by hgpu

Performance portability analysis of SYCL with a classical CG on CPU, GPU, and FPGA

Julian Franquinet

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Tags: Benchmarking, Computer science, CUDA, FPGA, nVidia, nVidia Quadro GP100, Optimization, Performance, performance portability, SYCL

October 22, 2023 by hgpu

Predicting the Execution Time of a kernel on a specific GPU using PTX code

Monika Dagar, Jorge Roldan

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 1650, nVidia GeForce GTX Titan XP, Performance, PTX, Tesla K20, Tesla K80, Tesla M60, Tesla P100, Tesla T4, Tesla V100

October 22, 2023 by hgpu

SYCL in the Edge: Performance Evaluation for Heterogeneous Acceleration

Youssef Faqir-Rhazoui, Carlos García

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia Jetson Nano, Optical flow, Package, SYCL

October 22, 2023 by hgpu

LeXInt: GPU-accelerated Exponential Integrators package

Pranab J. Deka, Alexander Moriggl, Lukas Einkemmer

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Tags: CUDA, Differential equations, Mathematics, nVidia, nVidia A100, Package

October 22, 2023 by hgpu

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

Peter Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio, Anton Gorenko, Michael M. Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A. Mitchell, Vijay S. Pande, João PGLM Rodrigues, Jaime Rodriguez-Guerra, Andrew C. Simmonett, Jason Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland

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Tags: AMD Radeon Pro V620, ATI, Chemical Physics, CUDA, HIP, Machine learning, Molecular dynamics, Molecular simulation, nVidia, nVidia A100, nVidia GeForce RTX 4080, OpenCL, Package, Physics

October 15, 2023 by hgpu

Open SYCL on heterogeneous GPU systems: A case of study

Rocío Carratalá-Sáez, Francisco J. andújar, Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, CUDA, Heterogeneous systems, HIP, nVidia, Package, performance portability, SYCL

October 15, 2023 by hgpu

Advancing the distributed Multi-GPU ChASE library through algorithm optimization and NCCL library

Xinzhe Wu, Edoardo Di Napoli

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Tags: Algorithm optimization, Computer science, CUDA, MPI, nVidia, nVidia A100, OpenMP, OpenMPI, Package

October 8, 2023 by hgpu

Impacts of Parallel Programming on Limited-Resource Hardware

Renato Barreto Hoffmann Filho

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming techniques, Thesis

October 8, 2023 by hgpu

Memory Efficient Mixed-Precision Optimizers

Basile Lewandowski, Atli Kosson

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Tags: Computer science, CUDA, Machine learning, Mixed precision, nVidia, nVidia A100, nVidia V100

October 1, 2023 by hgpu

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Shilei Tian, Tom Scogland, Barbara Chapman, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250, ATI, Benchmarking, Compilers, Computer science, CUDA, HIP, nVidia, nVidia A100, OpenMP, performance portability

October 1, 2023 by hgpu

Performance Study of GPU-based Joins

Efficiently Processing Large Relational Joins on GPUs

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

bib boi: Tools to help with LaTeX paper writing

Compiler-centric across-stack deep learning acceleration

Kernel Tuner

Testing and Mutation Testing for GPU Kernels

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP-AMD: Extending CUDA to AMD Platforms

gossip: Efficient Communication Primitives for Multi-GPU Systems

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

GT4Py: GridTools for Python

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

miniBUDE: A BUDE virtual-screening benchmark, in many programming models

Evaluation of FPGA-based high performance computing platforms

AUCMEDI: a framework for Automated Classification of Medical Images

Frameworks in Medical Image Analysis with Deep Neural Networks

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

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