Hardware Acceleration of High-Performance Computational Flow Dynamics Using High-Bandwidth Memory-Enabled Field-Programmable Gate Arrays

Scientific computing is at the core of many High-Performance Computing applications, including computational flow dynamics. Because of the utmost importance to simulate increasingly larger computational models, hardware acceleration is receiving increased attention due to its potential to maximize the performance of scientific computing....

On Hardware-Accelerated Maximally-Efficient Systolic Arrays: Acceleration and Optimization of Genomics Pipelines Through Hardware/Software Co-Design

Developments in sequencing technology have drastically reduced the cost of DNA sequencing. The raw sequencing data being generated requires processing through computationally demanding suites of bioinformatics algorithms called genomics pipelines. The greatly decreased cost of sequencing has resulted in its widespread adoption, and the amount of...

Hardware acceleration of BWA-MEM genomic short read mapping for longer read lengths

We present our work on hardware accelerated genomics pipelines, using either FPGAs or GPUs to accelerate execution of BWA-MEM, a widely-used algorithm for genomic short read mapping. The mapping stage can take up to 40% of overall processing time for genomics pipelines. Our implementation offloads the Seed Extension function, one of the main...

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the...

Power-Efficiency Analysis of Accelerated BWA-MEM Implementations on Heterogeneous Computing Platforms

Next Generation Sequencing techniques have dramatically reduced the cost of sequencing genetic material, resulting in huge amounts of data being sequenced. The processing of this data poses huge challenges, both from a performance perspective, as well as from a power-efficiency perspective. Heterogeneous computing can help on both fronts, by...

Computational Challenges of Next Generation Sequencing Pipelines Using Heterogeneous Systems

We are rapidly entering the era of genomics. The dramatic cost reduction of DNA sequencing due to the introduction of Next Generation Sequencing (NGS) techniques has resulted in an exponential growth of genetics data. The amount of data generated, and its associated processing into useful information, poses serious computational challenges. Here...