BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250822T115806Z
LOCATION:Room 6.0D13
DTSTART;TZID=Europe/Stockholm:20250616T143000
DTEND;TZID=Europe/Stockholm:20250616T163000
UID:submissions.pasc-conference.org_PASC25_sess136@linklings.com
SUMMARY:MS2D - Challenges in Systems Design for Omics
DESCRIPTION:This minisymposium aims to address the critical challenges fac
 ed in the design and implementation of systems for omics research. As the 
 field of omics, encompassing various disciplines such as genomics, proteom
 ics, and metabolomics, continues to expand rapidly, there is an increasing
  demand for hardware-software co-design and robust computational systems t
 hat can handle large datasets, provide accurate analyses, and facilitate m
 eaningful biological insights. The enormous data growth continuously shift
 s the life sciences from model-driven towards data-driven science driving 
 the adoption of deep neural network models, massively parallel accelerator
 s such as GPUs, and vendor-independent portability frameworks. This sessio
 n will bring together experts from both computational and life sciences to
  discuss innovative approaches to systems design that meet the unique need
 s of omics workloads. Topics will include advanced algorithms for data pro
 cessing in genomics and proteomics, novel data representations that achiev
 e superior memory efficiency, and hardware-software co-design to improve p
 erformance and energy efficiency. Mechanisms that enable real-time analysi
 s of genomic data by analyzing electrical signals as raw sequencing data, 
 lessons learned from GPU acceleration of computations in widely used bioin
 formatics tools, and an outlook on future software and hardware trends tha
 t will likely impact computational biology will be shared.\n\nAccelerating
  Protein Homology Search for AlphaFold on GPUs\n\nThe enormous data growth
  continuously shifts the life sciences from model-driven towards data-driv
 en science. The need for efficient processing has led to the adoption of m
 assively parallel accelerators such as GPUs. As a consequence, genomics an
 d proteomics method development nowadays often heavily...\n\n\nBertil Schm
 idt (Johannes Gutenberg University Mainz)\n---------------------\nAccelera
 ting AI-based Genome Analysis via Algorithm-Architecture Co-Design\n\nAnal
 yzing genomic data provides critical insights for understanding and treati
 ng diseases, outbreak tracing, evolutionary studies, agriculture, and many
  other areas of the life sciences and personalized medicine. Modern genome
  sequencing devices can rapidly generate large amounts of genomic data at 
 ...\n\n\nCan Firtina (ETH Zurich)\n---------------------\nComputational Bi
 ology Patterns as a Co-Design Resource and Proposed Technology Roadmap for
  Modernizing Workhorse Biomedical Codes\n\nApplication proxies in high-per
 formance computing play an important role for software/hardware co-design.
   To broaden the types of computation available for co-design, we are deve
 loping a suite of proxy apps based on MetaHipMer2 (mhm2), a DOE-developed,
  scalable, de novo metagenome assembler.  MetaH...\n\n\nAmy Powell (Sandia
  National Laboratories, University of New Mexico); Logan Williams (North C
 arolina State University); Jan Ciesko (Sandia National Laboratories); and 
 Gavin C. Conan (North Carolina State University)\n---------------------\nB
 uilding Ultra-Large Pangenomes\n\nPangenomics is an emerging field that is
  allowing us to accurately and comprehensively study the within-species ge
 netic diversity and its relationship to physical traits (phenotypes) by us
 ing a collection of genomes of a species instead of a single reference gen
 ome. Future pangenomics applications w...\n\n\nYatish Turakhia (University
  of California San Diego)\n\nDomain: Engineering, Life Sciences\n\nSession
  Chairs: Bertil Schmidt (Johannes Gutenberg University Mainz), Gagandeep S
 ingh (AMD), and Sriranjani Sitaraman (AMD)
END:VEVENT
END:VCALENDAR