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Length: 480
Rating: 0.00 (0 ratings)
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Disk-Based Parallel Computation, Rubik's Cube, and Checkpointing
Google Tech Talks
March, 24 2008
ABSTRACT
This talk takes us on a journey through three varied, but interconnected
topics. First, our research lab has engaged in a series of disk-based
computations extending over five years. Disks have traditionally
been used for filesystems, for virtual memory, and for databases.
Disk-based computation opens up an important fourth use: an abstraction
for multiple disks that allows parallel programs to treat them in a
manner similar to RAM. The key observation is that 50 disks have
approximately the same parallel bandwidth as a _single_ RAM subsystem.
This leaves latency as the primary concern. A second key is the use
of techniques like delayed duplicate detection to avoid latency. For
example, hash accesses accesses can be saved (even saved on disk), until
there are sufficiently many pending accesses to use standard streaming
techniques. We have designed a library for search problems that exploits
the high parallel bandwidth while hiding the latency. We build
abstractions for search that employ parallel disk-based hash arrays
with the same speed as a single hash array in a single RAM subsystem.
In the case of Rubik's cube, we exploited this mechanism by using
seven terabytes of distributed disk in a search problem that showed
that 26 moves suffice to solve Rubik's cube. Our initial efforts
emphasize idempotent operations, so that we can easily recover from
hardware or software faults. We next intend to apply a more general
solution for fault recovery: checkpointing. This separate effort
in our lab has now produced a mature, robust user-level checkpointing
program has now matured. The package works successfully in tests
on OpenMPI, MPICH-2, OpenMP, and parallel iPython (used in SciPy and
NumPy). Our DMTCP package transparently checkpoints parallel,
multi-threaded processes, with no modification either to the
operating system or to the application binaries. Extrapolating
from current experiments, we estimate that we can checkpoint a 1,000
node parallel computation in a matter of minutes. We are currently
searching for a testbed on which to demonstrate this scalability.
Speaker: Gene Cooperman
Length: 4433
Rating: 4.30 (18 ratings)
Tags: google techtalks techtalk engedu talk talks googletechtalks education
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A Search Engine Architecture Based on Collection Selection
Google Tech Talks
December, 19 2007
ABSTRACT
We present a distributed architecture for a Web search engine, based
on the concept of collection selection. We introduce a novel approach
to partition the collection of documents, able to greatly improve the
effectiveness of standard collection selection techniques (CORI), and
a new selection function outperforming the state of the art. Our
technique is based on the novel query-vector (QV) document model,
built from the analysis of query logs, and on our strategy of
co-clustering queries and documents at the same time.
By suitably partitioning the documents in the collection, our system
is able to select the subset of servers containing the most relevant
documents for each query. Instead of broadcasting the query to every
server in the computing platform, only the most relevant will be
polled, this way reducing the average computing cost to solve a query.
We introduce a novel strategy to use the instant load at each server
to drive the query routing. Also, we describe a new approach to
caching, able to incrementally improve the quality of the stored
results. Our caching strategy is effectively both in reducing
computing load and in improving result quality. The proposed
architecture, overall, presents a trade-off between computing cost and
result quality, and we show how to guarantee very precise results in
face of a dramatic reduction to computing load. This means that, with
the same computing infrastructure, our system can serve more users,
more queries and more documents.
Speaker: Diego Puppin
Length: 1981
Rating: 4.60 (5 ratings)
Tags: google techtalks techtalk engedu talk talks googletechtalks education
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GTAC 2007: H.Ziv & K.Windbladh - Specification based Testing
The 2nd Annual Google Test Automation Conference (GTAC) at our New York office.
Hadar Ziv and Kristina Windbladh. Specification-based Testing.
Professor Hadar Ziv, with the Bren School of Information and Computer Sciences (ICS) at UC Irvine, has 20+ years of experience in academia and industry. Most recently, he presented his work at Google, Northrop Grumman, and the Southern California SPIN, and served on the program committee of the ROSATEA 2007 workshop. His most recent papers appeared in ROSATEA 2007, 2006, and the October 2006 issue of the Journal of Systems and Software (JSS). He has worked as consultant and change agent for several organizations wishing to upgrade their software development to include use cases, object-oriented analysis and design with UML, and corresponding test strategies. Hadar has provided consulting, training and mentoring to, among others, the Capital Group Companies, Fidelity National Title, Logicon (now Northrop Grumman), Beckman Coulter, and most recently, St. Jude Medical (NYSE: SJM)
Kristina Winbladh is about to start her third year as a PhD student in Informatics at the University of California, Irvine. Her main research interests are in software testing and requirements engineering, and particularly in bridging the two disciplines with the goal of producing better quality software. During her first two years of graduate school, her attempts to improve software testing techniques has earned her several workshop and conference publications as well as an internship with Google.
Length: 3847
Rating: 4.00 (18 ratings)
Tags: GTAC 2007 Google Test Automation Conference Hadar Ziv Kristina Windbladh
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Impulse-based ultra-wide-band (UWB) radio systems and applications
Google Tech Talks
May 22, 2008
ABSTRACT
The old idea of impulse radio dates back to Marconi's first wireless transmissions using sparks. Unlike
most wireless today, impulse radio transmissions are extremely wideband signals. The recently FCC-
released frequency band from 3.1GHz to 10.6GHz is the widest unlicensed frequency band ever released (7.5GHz). This ultra wide bandwidth (UWB) is commercially explored for even faster data transfer using traditional, multi-band (OFDM) RF techniques. However, the available bandwidth is wide enough for impulse radio transmission giving new functionality and new implementation challenges.
In this talk I will show how power efficient impulse radio solutions are feasible in standard digital CMOS
technology. Quite non-standard and untraditional design strategies must be used including time-domain
signal processing. Circuit topologies for higher order Gaussian pulse generation and power efficient,
correlating RAKE receivers will be explained. Impulse radio transmissions have additional interesting properties compared to narrowband modulation.
With time-domain processing (TDOA) highly accurate positioning is feasible in the millimeter range. Improved sensitivity for robust communication. Large number of channels (greater than 100).
Novel applications are also feasible using impulse transmission. Combining novel design techniques like
"Swept-Threshold sampling" and digital lossless integration, micropower impulse radar is feasible in
CMOS. A 60GHz sampler is used to accumulate and recover reflected electromagnetic energy. These
new sensing devices (medical radar) may be explored for reading vital body signs (pulse, breathing, blood pressure?) embedded in your car seat or hospital emergency bed (detached sensor). Just imagine what you can do looking though heavy matter! Single chip CMOS impulse radar will be demonstrated at the end of the talk.
Speaker: Tor Sverre Lande
Tor Sverre (Bassen) Lande is a professor in Microelectronics at the Dept. of Informatics, Univ. of Oslo. From 2004 he is also serving as visiting professor at Institute of Biomedical Engineering, Imperial College, London, UK. His primary research is related to microelectronics, both digital and analog. Research fields are Neuromorphic Engineering, analog signal processing, micropower circuit design, biomedical circuits and systems and impulse radio. He is the author or co-author of more than 90 scientific publications with chapters in two books.
Length: 3727
Rating: 4.80 (16 ratings)
Tags: google techtalks techtalk engedu talk talks googletechtalks education
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Space Based Solar Power
This is an animation describing John Mankin's "sandwitch" concept, that was recently presented at the National Press Club in Washington DC by the NSS, and is part of the recent NSSO Study. You can read more at the NSS; http://www.nss.org/news/releases/pr20071010.html . This animation, and all derivatives are ©Mafic Studios, and permission must be obtained to use the content in any for-profit scenario. A 1080 HD version is available.
Length: 62
Rating: 4.80 (20 ratings)
Tags: space solar power sbsp ssp orbital
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Moveable Projected Displays using Projector Based Tracking
By using high-speed structured light patterns emitted by a project and embedded light sensors, we can discover the location and track objects in real-time. Project by Johnny Chung Lee - 2004
Length: 289
Rating: 4.90 (169 ratings)
Tags: projector calibration motion tracking augmented reality
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Forest-based Search Algorithms in Parsing and Machine Translation
Google Tech Talks
March, 14 2008
ABSTRACT
Many problems in Natural Language Processing (NLP) involves an
efficient search for the best derivation over (exponentially) many
candidates, especially in parsing and machine translation. In these
cases, the
concept of "packed forest" provides a compact representation of the
huge search spaces, where efficient inference algorithms based on
Dynamic Programming (DP) are possible.
In this talk we address two important open problems within this
framework: exact k-best inference which is often used in NLP
pipelines such as parse reranking and MT rescoring, and approximate
inference when the search space is too big for exact search.
We first present a series of fast and exact k-best algorithms on
forests, which are orders of magnitudes faster than previously used
methods on state-of-the-art parsers such as Collins (1999). We then
extend these algorithms for approximate search when the forests are
too big for exact inference. We discuss two particular instances of
this new method, forest rescoring for MT decoding with integrated
language models, and forest reranking for discriminative parsing. In
the former, our methods perform orders of magnitudes faster than
conventional beam search on both state-of-the-art phrase-based and
syntax-based systems, with the same level of search error or
translation quality. In the latter, faster search also leads to
better learning, where our approximate decoding makes whole-Treebank
discriminative training practical and results in the best accuracy to
date for parsers trained on the Treebank.
This talk includes joint work with David Chiang (USC Information
Sciences Institute).
Liang Huang (2008). Forest Reranking: Discriminative Parsing with Non-
Local Features.
Proceedings of ACL 2008 (to appear).
http://www.cis.upenn.edu/~lhuang3/forest-rerank.pdf
Liang Huang and David Chiang (2007). Forest Rescoring: Faster
Decoding with Integrated Language Models.
Proceedings of ACL 2007.
http://www.cis.upenn.edu/~lhuang3/acl-cube.pdf
Liang Huang and David Chiang (2005). Better k-best Parsing.
Proceedings of IWPT 2005.
http://www.cis.upenn.edu/~lhuang3/huang-iwpt-correct.pdf
Speaker: Liang Huang
Liang Huang is a final-year PhD student at the University of
Pennsylvania, co-supervised by Aravind Joshi and Kevin Knight (USC/
ISI). He is mainly interested in the theoretical aspects of
computational linguistics, in particular, efficient algorithms in
parsing and machine translation, generic dynamic programming, and
formal properties of synchronous grammars. He also works on applying
computational linguistics to structural biology.
Length: 3679
Rating: 4.80 (14 ratings)
Tags: google techtalks techtalk engedu talk talks googletechtalks education
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