Key Dates Full Papers

Submissions Deadline

January 24, 2019 AOE
January 14, 2019 AOE

Author Notification

March 4, 2019

Camera-Ready Papers Due

March 25, 2019
March 28, 2019

Key Dates Posters

Submissions Deadline

March 11, 2019
March 21, 2019

Author Notification

March 26, 2019

Camera-Ready Papers Due

April 1, 2019


Submission

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Submit your paper here


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Previous Conferences

2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004


General Co-Chairs

Francesca Palumbo
Università degli Studi di Sassari, IT
Michela Becchi
North Carolina State University, US

Program Co-Chairs

Martin Schulz
Technical University of Munich, DE
Kento Sato
RIKEN R-CCS, JP




For more information, visit the website at www.computingfrontiers.org
Computing Frontiers 2019 is proud to announce the following keynote speakers and talks this year:
  • Keynote 1: Catherine Graves
    High-performance, low power hardware accelerators: analog computation and content addressable memories with emerging devices
  • Keynote 2: To be annnounced!

High-performance, low power hardware accelerators: analog computation and content addressable memories with emerging devices

Dr. Catherine Graves, Hewlett Packard Labs, US

Bio:
Dr. Catherine Graves is a research scientist at Hewlett Packard Labs in Palo Alto, CA developing analog and neuromorphic computational accelerators which leverage emerging devices such as resistive RAM. These hardware accelerators are designed to overcome the limited energy efficiency and throughput of existing general-purpose digital approaches, particularly for data centric computations, by targeting bottlenecked computations and data movement. Currently, she leads a team developing an accelerator for finite automata, targeting regular expression matching at wire speeds for network intrusion detection systems. Previously, she developed an accelerator utilizing analog resistive RAM devices to natively perform vector-matrix multiplication, accelerating the core computation in wide-ranging applications from neural networks to signal processing. She received her Ph.D. in Applied Physics from Stanford University studying ultrafast magnetism for future magnetic memory technologies. She has published over 30 peer-reviewed papers, three book chapters and has several patent applications pending.



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