Aligning sequencing reads onto a reference is an essential step of the majority of genomic
analysis pipelines. Computational algorithms for read alignment have evolved in …

We now need more than ever to make genome analysis more intelligent. We need to read,
analyze, and interpret our genomes not only quickly, but also accurately and efficiently …

Modern computing systems are overwhelmingly designed to move data to computation. This
design choice goes directly against at least three key trends in computing that cause …

Disaggregated memory can address resource provisioning inefficiencies in current
datacenters. Multiple software runtimes for disaggregated memory have been proposed in …

Many modern and emerging applications must process increasingly large volumes of data.
Unfortunately, prevalent computing paradigms are not designed to efficiently handle such …

Genome sequence analysis has enabled significant advancements in medical and scientific
areas such as personalized medicine, outbreak tracing, and the understanding of evolution …

Read map** is a fundamental step in many genomics applications. It is used to identify
potential matches and differences between fragments (called reads) of a sequenced …

Modern data-intensive applications demand high computational capabilities with strict
power constraints. Unfortunately, such applications suffer from a significant waste of both …

Genome analysis fundamentally starts with a process known as read map**, where
sequenced fragments of an organism's genome are compared against a reference genome …

Ongoing climate change calls for fast and accurate weather and climate modeling. However,
when solving large-scale weather prediction simulations, state-of-the-art CPU and GPU …