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Exploring Scalability in C++ Parallel STL Implementations

Ruben Laso, Diego Krupitza, Sascha Hunold

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Ampere A2, OpenMP, Package, Performance, Tesla T4

September 1, 2024 by hgpu

Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

Daniele De Sensi, Lorenzo Pichetti, Flavio Vella, Tiziano De Matteis, Zebin Ren, Luigi Fusco, Matteo Turisini, Daniele Cesarini, Kurt Lust, Animesh Trivedi, Duncan Roweth, Filippo Spiga, Salvatore Di Girolamo, Torsten Hoefler

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, Computer science, CUDA, HPC, MPI, nVidia, nVidia A100, nVidia H100, Performance

September 1, 2024 by hgpu

A Comprehensive Deep Learning Library Benchmark and Optimal Library Selection

Qiyang Zhang, Xiangying Che, Yijie Chen, Xiao Ma, Mengwei Xu, Schahram Dustdar, Xuanzhe Liu, Shangguang Wang

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Tags: Benchmarking, Computer science, Deep learning, Heterogeneous systems, Package

August 14, 2024 by hgpu

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

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Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

Zhao Xu, Fan Liu, Hao Liu

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Tags: AI, Benchmarking, Computer science, nVidia, nVidia A800, Package, Security

June 16, 2024 by hgpu

Experiences with implementing Kokkos’ SYCL backend

Daniel Arndt, Damien Lebrun-Grandie, Christian Trott

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Tags: Benchmarking, Computer science, HPC, Intel, Intel Data Center GPU Max 1550, Package, performance portability

May 5, 2024 by hgpu

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

Peter Thoman, Philip Salzmann

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Tags: Benchmarking, Computer science, GPU cluster, HPC, nVidia, nVidia V100, Package, SYCL

April 14, 2024 by hgpu

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

Francesco Salvadore, Giacomo Rossi, Srikanth Sathyanarayana, Matteo Bernardini

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, cfd, Compression, Fluid dynamics, Intel, Intel Data Center GPU Max 1550, nVidia, nVidia A100, OpenMP

April 14, 2024 by hgpu

Parallel Gaussian process with kernel approximation in CUDA

Davide Carminati

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Tags: Benchmarking, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2080, Package

March 24, 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

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

Yehonatan Fridman, Guy Tamir, Uri Steinitz, Gal Oren

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Tags: Benchmarking, Intel, Intel Ponte Vecchio Max 1100, Monte Carlo simulation, OpenMP, Package, Physics

March 10, 2024 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

Exploring Scalability in C++ Parallel STL Implementations

Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

A Comprehensive Deep Learning Library Benchmark and Optimal Library Selection

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

Experiences with implementing Kokkos’ SYCL backend

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

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

Parallel Gaussian process with kernel approximation in CUDA

MUPPET: Optimizing Performance in OpenMP via Mutation Testing

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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