A critical step of genome sequence analysis is the map** of sequenced DNA fragments
(ie, reads) collected from an individual to a known linear reference genome sequence (ie …

There has been an arms race for devising accelerators for deep learning in recent years.
However, real-world applications are not only neural networks but often span across …

Designs generated by high-level synthesis (HLS) tools typically achieve a lower frequency
compared to manual RTL designs. In this work, we study the timing issues in a diverse set of …

As specialized hardware accelerators like FPGAs become a prominent part of the current
computing landscape, software applications are increasingly constructed to leverage …

Heterogeneous computing with field-programmable gate-arrays (FPGAs) has demonstrated
orders of magnitude improvement in computing efficiency for many applications. However …

Sequence alignment is the most time-consuming step in the genome analysis pipeline.
Since sequence alignment generally follows the seed-and-extension paradigm, prior …

In this paper, we propose a Hyper-Dimensional genome analysis platform. Instead of
working with original sequences, our method maps the genome sequences into high …

Genome sequencing is one of the key applications in healthcare and has a great potential to
realize precision medicine and personalized healthcare. However, its computing process is …

With the development of big data, machine learning, and AI, existing software engineering
techniques must be re-imagined to provide the productivity gains that developers desire …

The slowing of CMOS technology scaling mismatches the ever-increasing demand for
computational power, leading to a rise in the use of heterogeneous systems, which pair …