[hpc-announce] Accelerator Architecture in Computational Biology and Bioinformatics workshop @ HPCA-2019: Call for Papers

[Leonid Yavits]

2nd Accelerator Architecture in Computational Biology and Bioinformatics
workshop (AACBB-2019) 
February 16th, 2019 
In conjunction with 25th IEEE International Symposium on High-Performance
Computer Architecture (HPCA-2019) 
Washington D.C., USA

-> Workshop website           	https://aacbb-workshop.github.io/ 
-> Submission link
https://easychair.org/conferences/?conf=aacbb2019
-> Submission deadline       	December 25, 2018, EoD AoE 
-> Notifications			December 28, 2018

Invited Speakers
-> William Dally, Chief Scientist of NVIDIA, Stanford 
-> Onur Mutlu, ETH Zurich, CMU
-> Ananth Kalyanaraman, WSU

List of Topics
-> Impact of bioinformatics and biology applications on computer
architecture 
-> Bioinformatics and computational biology accelerator architecture and
design
-> 3D memory-logic stack based accelerators Automata processing in 
-> bioinformatics and computational biology applications
-> Associative processing in bioinformatics and computational biology
applications
-> Near-data (in-memory) acceleration of bioinformatics and 
-> computational biology applications
-> Emerging memory technologies and their impact on bioinformatics and
computational biology
-> Embedded and reconfigurable architectures Field programmable logic 
-> based accelerators Bioinformatics and computational biology-inspired 
-> hardware/software trade-offs
-> Software acceleration of computational biology and bioinformatics

	Over the last decade, the advent of high-throughput sequencing
techniques brought an exponential growth in biosequence database sizes. 
With increased throughput demand and popularity of computational biology
tools, reducing time-to-solution during computational analysis 
has become a significant challenge in the path to scientific discovery.

	Conventional computer architecture is proven to be inefficient for
computational biology and bioinformatics tasks. For example, aligning 
even several hundred DNA or protein sequences using progressive multiple
alignment tools consumes several CPU hours on high performance computer. 
Hence, computational biology and bioinformatics rely on hardware
accelerators to allow processing to keep up with the increasing amount 
of data generated from biology applications. In a typical application,
dominant portion of the runtime is spent in a small number of 
computational kernels, making it an excellent target for hardware
acceleration. The combination of increasingly large datasets and high 
performance computing requirements make computational biology prime
candidate to benefit from accelerator architecture research. 

	Potential directions include 3D integration, near-data processing,
automata processing, associative processing and reconfigurable
architectures.
This workshop will focus on architecture and design of hardware accelerators
for computational biology and bioinformatics problems. 
We plan to present and discuss a variety of acceleration techniques,
accelerator architectures and their implications on the development of
computational biology.


Important Notes
-> Presenting a paper in the workshop does not preclude publication in other
venues
-> We will have a poster session. Some papers might be accepted as 'poster'
papers. 
-> We plan to have a lightning round, where the authors of a poster paper
are given an opportunity 
to present their work to all attendants in a "lightning" 2min presentation.

Committees

Program Committee

-> Ananth Kalyanaraman, WSU
-> Can Alkan, Bilkent University
-> Engin Ipek, University of Rochester
-> Jason Cong, UCLA
-> Mattan Erez, UT Austin
-> Mircea Stan, UVA
-> Onur Mutlu, ETH
-> Ran Ginosar, Technion
-> Ronnie Ronen, Technion
-> Yuan Xie, UCSB

Organizing committee
-> Roman Kaplan (mailto:romankap at gmail.com) 
-> Leonid Yavits (mailto:leonid.yavits at gmail.com)