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update anatole, work on publications, add talks list

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Carl Pearson
2021-01-27 17:40:20 -07:00
parent 163a470f3f
commit 3a685bf1a6
28 changed files with 204 additions and 780 deletions
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content/publication/20171108_hwu_icrc.md
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@@ -3,28 +3,10 @@ title = "Rebooting the Data Access Hierarchy of Computing Systems"
date = 2017-11-18
draft = false
# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
authors = ["Wen-mei Hwu", "Izzat El Hajj", "Simon Garcia de Gonzalo", "Carl Pearson", "Nam Sung Kim", "Deming Chen", "Jinjun Xiong", "Zehra Sura"]
# Publication type.
# Legend:
# 0 = Uncategorized
# 1 = Conference paper
# 2 = Journal article
# 3 = Manuscript
# 4 = Report
# 5 = Book
# 6 = Book section
publication_types = ["0"]
# Publication name and optional abbreviated version.
publication = "In *Computing and Electromagnetics International Workshop*."
publication_short = "In *CEM*"
# Abstract and optional shortened version.
abstract = "In this paper, we present our view of massively-parallel heterogeneous computing for solving large scientific problems. We start by observing that computing has been the primary driver of major innovations since the beginning of the 21st century. We argue that this is the fruit of decades of progress in computing methods, technology, and systems. A high-level analysis on out-scaling and up-scaling on large supercomputers is given through a time-domain wave-scattering simulation example. The importance of heterogeneous node architectures for good up-scaling is highlighted. A case for low-complexity algorithms is made for continued scale-out towards exascale systems."
abstract_short = ""
# Is this a selected publication? (true/false)
selected = false
@@ -79,3 +61,7 @@ math = false
# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
focal_point = ""
+++
authors = ["Wen-mei Hwu", "Izzat El Hajj", "Simon Garcia de Gonzalo", "Carl Pearson", "Nam Sung Kim", "Deming Chen", "Jinjun Xiong", "Zehra Sura"]
In this paper, we present our view of massively-parallel heterogeneous computing for solving large scientific problems. We start by observing that computing has been the primary driver of major innovations since the beginning of the 21st century. We argue that this is the fruit of decades of progress in computing methods, technology, and systems. A high-level analysis on out-scaling and up-scaling on large supercomputers is given through a time-domain wave-scattering simulation example. The importance of heterogeneous node architectures for good up-scaling is highlighted. A case for low-complexity algorithms is made for continued scale-out towards exascale systems.