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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

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

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Xinyu Chen, Jiannan Tian, Ian Beaver, Cynthia Freeman, Yan Yan, Jianguo Wang, Dingwen Tao

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Tags: Benchmarking, Compression, Computer science, CUDA, Databases, HPC, nVidia, nVidia RTX 6000 Ada, Package, SYCL

December 24, 2023 by hgpu

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, Software Engineering

December 24, 2023 by hgpu

Comparative Performance and Scalability Analysis of GPU-accelerated Database Operations

Carl Andersson, Jonathan Nilsson

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A10, nVidia M60, Performance, Tesla T4, Thesis

December 24, 2023 by hgpu

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

Konstantinos Parasyris, Giorgis Georgakoudis, Esteban Rangel, Ignacio Laguna, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250X, ATI, Auto-Tuning, Computer science, Heterogeneous systems, nVidia, nVidia V100, OpenMP, Package

December 18, 2023 by hgpu

cuSZ-I: High-Fidelity Error-Bounded Lossy Compression for Scientific Data on GPUs

Jinyang Liu, Jiannan Tian, Shixun Wu, Sheng Di, Boyuan Zhang, Yafan Huang, Kai Zhao, Guanpeng Li, Dingwen Tao, Zizhong Chen, Franck Cappello

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Tags: Compression, Computer science, CUDA, nVidia, nVidia A100, nVidia A40

December 18, 2023 by hgpu

Principles for Automated and Reproducible Benchmarking

Tuomas Koskela, Ilektra Christidi, Mosè Giordano, Emily Dubrovska, Jamie Quinn, Christopher Maynard, Dave Case, Kaan Olgu, Tom Deakin

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Tags: Benchmarking, Computer science, HPC, nVidia, oneAPI, Package, performance portability

December 18, 2023 by hgpu

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Wenhua Yang, Chong Zhang, Minxue Pan

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming Languages, survey

December 10, 2023 by hgpu

Efficiently Processing Large Relational Joins on GPUs

Bowen Wu, Dimitrios Koutsoukos, Gustavo Alonso

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

December 10, 2023 by hgpu

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

Monica Dessole, Jolly Chen, Axel Naumann

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Tags: CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3060, nVidia L4, oneAPI, Package, Performance, Physics, SYCL

December 10, 2023 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

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

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

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

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high performance computing on graphics processing units: hgpu.org

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

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

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

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Comparative Performance and Scalability Analysis of GPU-accelerated Database Operations

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

cuSZ-I: High-Fidelity Error-Bounded Lossy Compression for Scientific Data on GPUs

Principles for Automated and Reproducible Benchmarking

Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Efficiently Processing Large Relational Joins on GPUs

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

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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