Past Meetup

Parallel computation with molecular-motor-propelled agents (...)

This Meetup is past

6 people went

Every 2 months on the 4th Wednesday

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Details

Happy 2017, and welcome to the DC/NoVA Papers We Love meetup!

Papers We Love is an international organization centered around the appreciation of computer science research papers. There's so much we can learn from the landmark research that shaped the field and the current studies that are shaping our future. Our goal is to create a community of tech professionals passionate about learning and sharing knowledge. Come join us!

New to research papers? Watch The Refreshingly Rewarding Realm of Research Papers (https://www.youtube.com/watch?v=8eRx5Wo3xYA) by Sean Cribbs.

Ideas and suggestions are welcome–fill our our interest survey here (https://docs.google.com/forms/d/e/1FAIpQLSeJwLQhnmzWcuyodPrSmqHgqrvNxRbnNSbiWAuwzHwshhy_Sg/viewform) and let us know what motivates you!

// Tentative Schedule

• 7:00-7:30–Informal paper discussion

• 7:30-7:35–Introduction and announcements

• 7:35-8:30–Parallel computation with molecular-motor-propelled agents in nanofabricated networks (http://www.pnas.org/content/113/10/2591), presented by Sam DeLuca (details below)

// Directions

We'll be meeting in Meeting Room 1/2 of Woodrow Wilson Library (http://www.fairfaxcounty.gov/library/branches/ww/)! There's plenty of parking, and there are several buses that come to the library from local metro stops.

If you're late, we totally understand–please still come! Just be sure to slip in quietly if a speaker is presenting.

// Papers

• Parallel computation with molecular-motor-propelled agents in nanofabricated networks by Dan V. Nicolau, Jr. (https://www.mcgill.ca/bioengineering/people/faculty/dan-nicolau), et al
Presented by Sam DeLuca

homepage (http://www.pnas.org/content/113/10/2591) | pdf (http://www.pnas.org/content/113/10/2591.full.pdf)

Research Significance: Electronic computers are extremely powerful at performing a high number of operations at very high speeds, sequentially. However, they struggle with combinatorial tasks that can be solved faster if many operations are performed in parallel. Here, we present proof-of-concept of a parallel computer by solving the specific instance {2, 5, 9} of a classical nondeterministic-polynomial-time complete (“NP-complete”) problem, the subset sum problem. The computer consists of a specifically designed, nanostructured network explored by a large number of molecular-motor-driven, protein filaments. This system is highly energy efficient, thus avoiding the heating issues limiting electronic computers. We discuss the technical advances necessary to solve larger combinatorial problems than existing computation devices, potentially leading to a new way to tackle difficult mathematical problems.

About Sam: Sam DeLuca is a software engineer at CloudLock (https://www.cloudlock.com/), a cloud security company based in Massachusetts, where he works on task scheduling and messaging infrastructure. His background is in bioinformatics, including work on Rosetta (https://www.rosettacommons.org/), a molecular modeling system.