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Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Zhuren Liu, Shouzhe Zhang, Justin Garrigus, Hui Zhao

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, CUDA, Genomics, nVidia, nVidia GeForce RTX 3070, Package

May 28, 2023 by hgpu

An Asynchronous Dataflow-Driven Execution Model For Distributed Accelerator Computing

Philip Salzmann, Fabian Knorr, Peter Thoman, Philipp Gschwandtner, Biagio Cosenza, Thomas Fahringer

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

May 21, 2023 by hgpu

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Yueming Hao, Xu Zhao, Bin Bao, David Berard, Will Constable, Adnan Aziz, Xu Liu

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Tags: AMD Radeon Instinct MI210, ATI, Benchmarking, Computer science, Deep learning, nVidia, nVidia A100, Package, PyTorch

May 14, 2023 by hgpu

Performance Optimization using Multimodal Modeling and Heterogeneous GNN

Akash Dutta, Jordi Alcaraz, Ali TehraniJamsaz, Eduardo Cesar, Anna Sikora, Ali Jannesari

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Tags: AMD Radeon HD 7970, ATI, Benchmarking, Computer science, Deep learning, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX 970, OpenCL, OpenMP

May 14, 2023 by hgpu

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Yanwen Xu, Ang Li, Tyler Sorensen

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, HLS, Intel UHD 630, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, Package, Performance, SYCL

May 7, 2023 by hgpu

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs

Taabish Jeshani

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, Package, Performance, Thesis

May 7, 2023 by hgpu

Optimizing High-Performance Linpack for Exascale Accelerated Architectures

Noel Chalmers, Jakub Kurzak, Damon McDougall, Paul T. Bauman

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, Computer science, Factorization, HIP, Linear Algebra, MPI, Package, Performance

April 23, 2023 by hgpu

Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Zheming Jin, Jeffrey S. Vetter

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Tags: Benchmarking, Bioinformatics, Computer science, CUDA, Heterogeneous systems, nVidia, Package, performance portability, SYCL, Tesla V100

April 16, 2023 by hgpu

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

Yehonatan Fridman, Guy Tamir, Gal Oren

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Tags: Benchmarking, Computer science, Intel, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, oneAPI, OpenMP, Package, performance portability

April 16, 2023 by hgpu

Comparing SYCL data transfer strategies for tracking use cases

S.Joube, H. Grasland, D. Chamont, E.Brunet

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Tags: Benchmarking, Computer science, Memory model, nVidia, nVidia Quadro RTX 5000, SYCL

March 26, 2023 by hgpu

Towards a Benchmarking Suite for Kernel Tuners

Jacob O. Tørring, Ben van Werkhoven, Filip Petrovic, Floris-Jan Willemsen, Jirí Filipovic, Anne C. Elster

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Tags: Auto-Tuning, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3060, nVidia GeForce RTX 3090, nVidia Titan RTX, Package, performance portability

March 19, 2023 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

An Asynchronous Dataflow-Driven Execution Model For Distributed Accelerator Computing

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Performance Optimization using Multimodal Modeling and Heterogeneous GNN

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs

Optimizing High-Performance Linpack for Exascale Accelerated Architectures

Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

Comparing SYCL data transfer strategies for tracking use cases

Towards a Benchmarking Suite for Kernel Tuners

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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