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Seer: Predictive Runtime Kernel Selection for Irregular Problems

Ryan Swann, Muhammad Osama, Karthik Sangaiah, Jalal Mahmud

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, Linear Algebra, load balancing, Performance, Sparse matrix

April 7, 2024 by hgpu

Full-Scale File System Acceleration on GPU

Peter Maucher, Lennard Kittner, Nico Rath, Gregor Lucka, Lukas Werling, Yussuf Khalil, Thorsten Gröninger, Frank Bellosa

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Tags: AMD Radeon RX 6800, ATI, Computer science, Data Structures and Algorithms, HIP, Performance

March 24, 2024 by hgpu

Retargeting and Respecializing GPU Workloads for Performance Portability

Ivan R. Ivanov, Oleksandr Zinenko, Jens Domke, Toshio Endo, William S. Moses

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Tags: AMD Radeon Instinct MI210, AMD Radeon RX 6800, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia RTX A4000, Package, performance portability

March 24, 2024 by hgpu

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

John Tramm, Paul Romano, Patrick Shriwise, Amanda Lund, Johannes Doerfert, Patrick Steinbrecher, Andrew Siegel, Gavin Ridley

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Intel, Intel Data Center GPU Max 1550, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenMP, Package, performance portability

March 24, 2024 by hgpu

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

Xinyi Li, Ang Li, Bo Fang, Katarzyna Swirydowicz, Ignacio Laguna, Ganesh Gopalakrishnan

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, Hardware Architecture, HPC, Matrix multiplication, nVidia, nVidia A100, nVidia H100, nVidia V100, PTX

March 10, 2024 by hgpu

Hybrid quantum programming with PennyLane Lightning on HPC platforms

Ali Asadi, Amintor Dusko, Chae-Yeun Park, Vincent Michaud-Rioux, Isidor Schoch, Shuli Shu, Trevor Vincent, Lee James O'Riordan

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Tags: AMD Radeon Instinct MI250X, ATI, HPC, nVidia, nVidia A100, OpenMP, Package, Physics, Quantum Physics

March 10, 2024 by hgpu

SYCL-Bench 2020: Benchmarking SYCL 2020 on AMD, Intel, and NVIDIA GPUs

Luigi Crisci, Lorenzo Carpentieri, Peter Thoman, Aksel Alpay, Vincent Heuveline, Biagio Cosenza

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, Heterogeneous systems, HPC, Intel, Intel Ponte Vecchio Max 1100, nVidia, oneAPI, Portability, SYCL, Tesla V100

March 10, 2024 by hgpu

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Sébastien Darche, Michel R. Dagenais

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, Package, Performance, Profiling

March 3, 2024 by hgpu

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Manuel Costanzo, Enzo Rucci, Carlos García-Sanchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computational biology, CUDA, Heterogeneous systems, Intel Arc A770, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, nVidia V100, oneAPI, Package, Sequence alignment, SYCL

February 25, 2024 by hgpu

Graphtoy: Fast Software Simulation of Applications for AMD’s AI Engines

Jonathan Strobl, Leonardo Solis-Vasquez, Yannick Lavan, Andreas Koch

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Tags: ATI, Computer science, FPGA, molecular docking, Package

February 18, 2024 by hgpu

An Evaluative Comparison of Performance Portability across GPU Programming Models

Joshua H. Davis, Pranav Sivaraman, Isaac Minn, Konstantinos Parasyris, Harshitha Menon, Giorgis Georgakoudis, Abhinav Bhatele

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct Mi50, ATI, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia V100, OpenACC, OpenMP, Performance, performance portability, SYCL

February 18, 2024 by hgpu

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Ka Hei Martin Kwok, Matti Kortelainen, Giuseppe Cerati, Alexei Strelchenko, Oliver Gutsche, Allison Reinsvold Hall, Steve Lantz, Michael Reid, Daniel Riley, Sophie Berkman, Seyong Lee, Hammad Ather, Boyana Norris, Cong Wang

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Tags: AMD Radeon Instinct MI100, ATI, HEP, Intel, Intel Arc A770, nVidia, nVidia A100, nVidia V100, OpenMP, performance portability, Physics, SYCL

January 28, 2024 by hgpu

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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