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Preliminary report: Initial evaluation of StdPar implementations on AMD GPUs for HPC

Wei-Chen Lin, Simon McIntosh-Smith, Tom Deakin

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Tags: AMD Radeon Instinct MI100, AMD Radeon VII, Computer science, Heterogeneous systems, HIP, nVidia, OpenCL, Performance, SYCL

January 14, 2024 by hgpu

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Foteini Strati, Xianzhe Ma, Ana Klimovic

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia A100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

Code Generation for a Variety of Accelerators for a Graph DSL

Ashwina Kumar, M. Venkata Krishna, Prasanna Bartakke, Rahul Kumar, Rajesh Pandian M, Nibedita Behera, Rupesh Nasre

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Tags: Code generation, Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 2080 Ti, OpenACC, OpenCL, Package, SYCL, Tesla V100

January 14, 2024 by hgpu

Deep Learning for Obfuscated Code Analysis

Alexander Shroyer

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2060, OpenCL, Package, PyTorch, Thesis

January 7, 2024 by hgpu

UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework

Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

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Tags: Computer science, CUDA, Deep learning, FPGA, nVidia, OpenCL, Security, Tesla T4

January 7, 2024 by hgpu

Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks

Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Mihai Capota, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren

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Tags: AI, Code generation, Computer science, Heterogeneous systems, HPC, nVidia, nVidia A40, OpenMP, Package, Python

January 7, 2024 by hgpu

An Autonomous Data Language

Tom T.P. Franken, Thomas Neele, Jan Friso Groote

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Programming Languages

January 7, 2024 by hgpu

Optimization of Ported CFD Kernels on Intel Data Center GPU Max 1550 using oneAPI ESIMD

Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Christoph Bauinger, Xiao Zhu

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Tags: cfd, CUDA, Fluid dynamics, Intel, Intel Data Center GPU Max 1550, nVidia, nVidia A100, oneAPI, Performance, SYCL

December 31, 2023 by hgpu

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Aristotle Martin, Geng Liu, William Ladd, Seyong Lee, John Gounley, Jeffrey Vetter, Saumil Patel, Silvio Rizzi, Victor Mateevitsi, Joseph Insley, Amanda Randles

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, CUDA, Fluid dynamics, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia V100, performance portability, SYCL

December 31, 2023 by hgpu

Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsim

Stefano Markidis

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Tags: AMD Radeon Instinct MI250X, Computer science, CUDA, HIP, nVidia, nVidia A100, Quantum computing

December 31, 2023 by hgpu

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

Robbert Gurdeep Singha, Christophe Scholliers

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, OpenCL, Package, Programming Languages

December 31, 2023 by hgpu

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

Zejia Lin, Zewei Mo, Xuanteng Huang, Xianwei Zhang, Yutong Lu

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Tags: Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia A100, Task scheduling

December 24, 2023 by hgpu

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

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

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

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