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InTheLoop | 08.29.2011

August 29, 2011

Computers and Networks Catch a Young Supernova

A supernova discovered by Berkeley Lab’s Peter Nugent is closer to Earth—approximately 21 million light-years away—than any other of its kind in a generation. Astronomers believe they caught the supernova within hours of its explosion, a rare feat made possible by a specialized survey telescope and state-of-the-art computational tools. Astronomers say this event is an "instant cosmic classic.” Read more.

Jim Demmel Offers Course in Communication-Avoiding Algorithms

Jim Demmel, Professor of Mathematics and Computer Science at UC Berkeley with a joint appointment in Berkeley Lab’s Computational Research Division, is teaching a course in Communication-Avoiding Algorithms for the fall semester. Class is held Fridays from 12:00 to 2:00 pm in 405 Soda Hall.

Communication-avoiding algorithms will play a key role in progress toward exascale computing. Here is the course description:

Algorithms have two costs: arithmetic and communication. The communication cost represents the time (or energy) of moving data, either between levels of a memory hierarchy, or between processors over a network. The communication cost of an algorithm often dominates arithmetic cost, and technological trends indicate this cost gap will increase on a variety of platforms, from cloud computing to supercomputers to mobile devices. Therefore, we seek algorithms that greatly reduce, and if possible provably minimize, communication.

This course will address recent progress and open problems in minimizing communication. Topics, and potential class projects, include theory (communication lower bounds, devising new algorithms that greatly reduce or even minimize communication), software (automating the construction of new algorithms to minimize communication), hardware (understanding what technological trends mean for algorithm design, and vice-versa), and applications (using better algorithms in important applications).

The kinds of algorithms for which lower bounds, new algorithms, software generation and/or hardware trends will be discussed include dense and sparse linear algebra, FFTs, operations on structured and unstructured meshes, graph algorithms, sorting, searching and dynamic programming (depending on student interest).

The course will involve reading introductory material as well as some more advanced papers, and then either doing a related project or presenting a paper in class.

Magic Numbers: The Beauty of Decimal Notation

While adding up your grocery bill in the supermarket, you’re probably not thinking how important or sophisticated our number system is. But the discovery of the present system, by unknown mathematicians in India roughly 2,000 years ago — and shared with Europe from the 13th century onwards — was pivotal to the development of our modern world. Perhaps because we learn decimal arithmetic so early, we consider it trivial. In reality, decimal arithmetic is anything but trivial, since it eluded the best minds of the ancient world.

CRD’s Complex Systems Group Leader David Bailey and his frequent collaborator Jon Borwein discuss the historical significance of decimal arithmetic in an article titled “Magic Numbers: The Beauty of Decimal Notation,” published in The Conversation, an Australian online research forum. This article was adapted from a longer piece written by Jon and David for their blog Math Drudge.

This Week’s Computing Sciences Seminars

Par Lab Seminar Series: GreenDroid: An Architecture for the Dark Silicon Era
Thursday, Sept. 1, 11:00 am–12:30 pm, Wozniak Lounge, 438 Soda Hall, UC Berkeley
Michael Taylor, UC San Diego

The Dark Silicon Era kicked off with the transition to multicore and will be characterized by a wild chase for seemingly ever-more insane architectural designs. At the heart of this transformation is the utilization wall, which states that, with each new process generation, the percentage of transistors that a chip can switch at full frequency is dropping exponentially due to power constraints. This has led to increasingly larger and larger fractions of a chip’s silicon area that must remain passive, or dark.

Our research attacks this dark silicon problem directly through a set of energy-saving accelerators, called Conservation Cores, or c-cores. C-cores are a post-multicore approach that constructively uses dark silicon to reduce the energy consumption of an application by 10x or more. To examine the utility of c-cores, we are developing GreenDroid, a multicore chip that targets the Android mobile stack. Our mobile application processor prototype targets a 32-nm process and is comprised of hundreds of automatically generated, specialized, patchable c-cores. These cores target specific Android hotspots, including the kernel. Our preliminary results suggest that we can attain an average 7x improvement in energy efficiency using a modest 7 mm2 of silicon.

About Computing Sciences at Berkeley Lab

The Lawrence Berkeley National Laboratory (Berkeley Lab) Computing Sciences organization provides the computing and networking resources and expertise critical to advancing the Department of Energy's research missions: developing new energy sources, improving energy efficiency, developing new materials and increasing our understanding of ourselves, our world and our universe.

ESnet, the Energy Sciences Network, provides the high-bandwidth, reliable connections that link scientists at 40 DOE research sites to each other and to experimental facilities and supercomputing centers around the country. The National Energy Research Scientific Computing Center (NERSC) powers the discoveries of 7,000-plus scientists at national laboratories and universities, including those at Berkeley Lab's Computational Research Division (CRD). CRD conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture and high-performance software implementation. NERSC and ESnet are Department of Energy Office of Science User Facilities.

Lawrence Berkeley National Laboratory addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the DOE’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.