high performance computing on graphics processing units: hgpu.org

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Engineering Supercomputing Platforms for Biomolecular Applications

Robert Welch, Charles Laughton, Oliver Henrich, Tom Burnley, Daniel Cole, Alan Real, Sarah Harris, James Gebbie-Rayet

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct MI300X, ATI, Benchmarking, Biology, Biomolecules, Computational biology, CUDA, HPC, Molecular dynamics, nVidia, nVidia A100, nVidia GH200, nVidia H100, Package, Physics, ROCm, Tesla V100

June 22, 2025 by hgpu

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

Manuel Costanzo, Enzo Rucci, Carlos García-Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computer science, CUDA, Databases, Heterogeneous systems, HPC, Intel, Intel Arc A770, Intel UHD 630, Intel UHD 770, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Package, performance portability, SYCL, Tesla V100

December 15, 2024 by hgpu

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

Bertil Schmidt, Felix Kallenborn, Alexander Wichmann, Alejandro Chacon, Christian Hundt

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Tags: Bioinformatics, Biology, Computer science, CUDA, FPGA, Genomics, nVidia, nVidia A100, nVidia H100, nVidia L4, nVidia L40s, nVidia V100, Package

November 24, 2024 by hgpu

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

Arturo Gonzalez-Escribano, Diego García-Álvarez, Jesús Cámara

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Tags: Bioinformatics, Biology, CUDA, MPI, nVidia, nVidia A100, nVidia GeForce GTX Titan X, nVidia GeForce RTX 4050, OpenCL, Optimization, Sequence alignment

September 15, 2024 by hgpu

From GPUs to AI and quantum: three waves of acceleration in bioinformatics

Bertil Schmidt, Andreas Hildebrandt

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Tags: Artificial intelligence, Bioinformatics, Biology, Chemistry, Neural networks, Quantum computing

May 20, 2024 by hgpu

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Manuel Costanzo, Enzo Rucci, Carlos García-Sanchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computational biology, CUDA, Heterogeneous systems, Intel Arc A770, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, nVidia V100, oneAPI, Package, Sequence alignment, SYCL

February 25, 2024 by hgpu

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

Robin Kobus

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Tags: Bioinformatics, Biology, CUDA, Databases, Hashing, nVidia, nVidia Quadro GV100, Package, Sequence alignment, Tesla P100, Tesla V100, Thesis

November 27, 2023 by hgpu

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

Leonard Apanasevich, Yogesh Kale, Himanshu Sharma, Ana Marija Sokovic

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Tags: Benchmarking, Bioinformatics, Biology, Chemistry, Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, OpenMP, Performance, SYCL

November 5, 2023 by hgpu

Experience Migrating OpenCL to SYCL: A Case Study on Searches for Potential Off-Target Sites of Cas9 RNA-Guided Endonucleases on AMD GPUs

Zheming Jin, Jeffrey S. Vetter

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI60, AMD Radeon VII, ATI, ATI Radeon HD 7870, Bioinformatics, Biology, OpenCL, performance portability, RNA, SYCL

October 1, 2023 by hgpu

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, ATI, Bioinformatics, Biology, Computer science, CUDA, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Programming Languages, Smith-Waterman algorithm, SYCL, Tesla V100

September 24, 2023 by hgpu

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Hyun Park, Parth Patel, Roland Haas, E. A. Huerta

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Tags: AI, Algorithms, Biology, Biomolecules, Biophysics, nVidia, nVidia A100, nVidia A40, Package

August 20, 2023 by hgpu

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Yu Zhou, Justin Sonneck, Sweta Banerjee, Stefanie Dörr, Anika Grüneboom, Kristina Lorenz, Jianxu Chen

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Tags: Artificial intelligence, Biology, Computer science, CUDA, nVidia, nVidia Quadro RTX 4000, Package

June 18, 2023 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

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high performance computing on graphics processing units: hgpu.org

Engineering Supercomputing Platforms for Biomolecular Applications

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

From GPUs to AI and quantum: three waves of acceleration in bioinformatics

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

Experience Migrating OpenCL to SYCL: A Case Study on Searches for Potential Off-Target Sites of Cas9 RNA-Guided Endonucleases on AMD GPUs

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

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