6533b871fe1ef96bd12d227f
RESEARCH PRODUCT
Accelerating bioinformatics applications via emerging parallel computing systems [Guest editorial]
Bertil SchmidtJuan A. Gómez-pulidoWu-chun Fengsubject
Focus (computing)Parallelism (rhetoric)Computer sciencebusiness.industryApplied MathematicsCloud computingParallel computingBioinformaticsComputing MethodologiesGeneticsData-intensive computingUnconventional computingbusinessField-programmable gate arrayMassively parallelBiotechnologydescription
The papers in this issue focus on advanced parallel computing systems for bioinformatics applications. This papers provide a forum to publish recent advances in the improvement of handling bioinformatics problems on emerging parallel computing systems. These systems can be characterized by exploiting different types of parallelism, including fine-grained versus coarse-grained and thread-level parallelism versus datalevel parallelism versus request-level parallelism. Hence, parallel computing systems based on multi- and many-core CPUs, many-core GPUs, vector processors, or FPGAs offer the promise to massively accelerate many bioinformatics algorithms and applications, ranging from computeintensive to data-intensive. Such computing systems are increasingly ubiquitous, ranging from “big iron” datacenter supercomputers and datacenter cloud computing down to GPU-accelerated smartphones and laptops.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-09-01 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |