Protein sequence pattern matching: Leveraging application specific hardware accelerators

Sagi Manole, Amit Golander, Shlomo Weiss

Research output: Contribution to journalArticlepeer-review


Digitalization has brought a tremendous momentum to health care research. Recognition of patterns in proteins is crucial for identifying possible functions of newly discovered proteins, as well as analysis of known proteins for previously undetermined activity. In this paper, the workload consists of locating patterns from the PROSITE database in protein sequences. We optimize the pattern search task by using a new breed of processors that merge network and server attributes. We leverage massive multithreading and regular-expression (RegX) hardware accelerators; the latter were designed and built for an entirely different applicationâhigh-bandwidth deep-packet inspection. Our multithreading optimization achieves 18Ã improvement, but by harnessing a RegX accelerator we were able to further demonstrate a significant 392Ã improvement relative to software pattern matching. Moreover, performance per area and power consumption are improved by multiple orders of magnitude as well.

Original languageEnglish
Article number6257365
Pages (from-to)448-460
Number of pages13
JournalIEEE Transactions on Computers
Issue number2
StatePublished - Feb 2014


  • CMP
  • Protein sequence
  • SMT
  • hardware accelerator
  • multithreading
  • pattern matching


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