Evidence map›Paper›PMID 39488701›Full record

ArticleBMC bioinformatics2024

CUDASW++4.0: ultra-fast GPU-based Smith-Waterman protein sequence database search.

Bertil Schmidt, Felix Kallenborn, Alejandro Chacon, Christian Hundt

Abstract read
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Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
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5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Bertil SchmidtDepartment of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany. bertil.schmidt@uni-mainz.de.
Felix KallenbornDepartment of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
Alejandro ChaconNVIDIA Corp., Santa Clara, USA.
Christian HundtNVIDIA Corp., Santa Clara, USA.

Funding

Deutsche Forschungsgemeinschaft 439669440 TRR319 RMaP TP C01
6 · The paper itself

Abstract

backgroundThe maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, current state-of-the-art software tools are not able to leverage the massively parallel processing capabilities of modern GPUs with close-to-peak performance. This motivates the need for more efficient implementations.

resultsCUDASW++4.0 is a fast software tool for scanning protein sequence databases with the Smith-Waterman algorithm on CUDA-enabled GPUs. Our approach achieves high efficiency for dynamic programming-based alignment computation by minimizing memory accesses and instructions. We provide both efficient matrix tiling, and sequence database partitioning schemes, and exploit next generation floating point arithmetic and novel DPX instructions. This leads to close-to-peak performance on modern GPU generations (Ampere, Ada, Hopper) with throughput rates of up to 1.94 TCUPS, 5.01 TCUPS, 5.71 TCUPS on an A100, L40S, and H100, respectively. Evaluation on the Swiss-Prot, UniRef50, and TrEMBL databases shows that CUDASW++4.0 gains over an order-of-magnitude performance improvements over previous GPU-based approaches (CUDASW++3.0, ADEPT, SW#DB). In addition, our algorithm demonstrates significant speedups over top-performing CPU-based tools (BLASTP, SWIPE, SWIMM2.0), can exploit multi-GPU nodes with linear scaling, and features an impressive energy efficiency of up to 15.7 GCUPS/Watt.

conclusionCUDASW++4.0 changes the standing of GPUs in protein sequence database search with Smith-Waterman alignment by providing close-to-peak performance on modern GPUs. It is freely available at https://github.com/asbschmidt/CUDASW4 .

Indexed as

AlgorithmsDatabases, ProteinSoftwareComputational BiologyComputer GraphicsProteinsSequence AlignmentSequence Analysis, ProteinProteinsCUDADPXDynamic programmingGPUProtein sequence database searchSmith–Waterman

Identifiers

PMID39488701
PMCPMC11531700

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.