high performance computing on graphics processing units: hgpu.org

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Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

Zachary Cooper-Baldock, Brenda Vara Almirall, Kiao Inthavong

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Tags: cfd, Fluid dynamics, HPC, MPI, nVidia, nVidia A100, nVidia V100, Performance

April 7, 2024 by hgpu

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

Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionality

Adrian Perez Dieguez, Min Choi, Mahmut Okyay, Mauro Del Ben, Bryan M. Wong, Khaled Z. Ibrahim

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Tags: Computer science, CUDA, HPC, MPI, nVidia, nVidia A100, OpenMP, Performance

March 18, 2024 by hgpu

MUPPET: Optimizing Performance in OpenMP via Mutation Testing

Dolores Miao, Ignacio Laguna, Giorgis Georgakoudis, Konstantinos Parasyris, Cindy Rubio-González

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Tags: Benchmarking, Computer science, OpenMP, Performance

March 18, 2024 by hgpu

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

Youssef Faqir-Rhazoui, Carlos García

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Tags: Computer science, CUDA, nVidia, nVidia Jetson Orin Nano, Optical flow, Package, Performance, SYCL

March 18, 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

Analyzing GPU Performance in Virtualized Environments: A Case Study

Adel Belkhiri, Michel Dagenais

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Tags: Computer science, CUDA, Java, nVidia, OpenCL, Package, Performance, Virtualization

February 25, 2024 by hgpu

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

Weile Luo, Ruibo Fan, Zeyu Li, Dayou Du, Qiang Wang, Xiaowen Chu

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia GeForce RTX 4090, nVidia H800, Performance, PTX

February 25, 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

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Gianmarco Accordi, Davide Gadioli, Emanele Vitali, Luigi Crisci, Biagio Cosenza, Andrea Beccari, Gianluca Palermo

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Tags: Computer science, CUDA, HPC, molecular docking, nVidia, nVidia A100, oneAPI, Performance, SYCL

February 12, 2024 by hgpu

Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame

Jolly Chen, Monica Dessole, Ana Lucia Varbanescu

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Tags: CUDA, HEP, nVidia, nVidia Quadro RTX 4000, OpenCL, Package, Performance, Physics, SYCL

January 28, 2024 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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high performance computing on graphics processing units: hgpu.org

Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

Seer: Predictive Runtime Kernel Selection for Irregular Problems

Full-Scale File System Acceleration on GPU

Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionality

MUPPET: Optimizing Performance in OpenMP via Mutation Testing

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

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Analyzing GPU Performance in Virtualized Environments: A Case Study

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

An Evaluative Comparison of Performance Portability across GPU Programming Models

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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