UC Santa Cruz Center for Information Technology Research in the Interest of Society Jim Demmel, Chief Scientist EECS and Math Depts. www.citris.berkeley.edu.
Download ReportTranscript UC Santa Cruz Center for Information Technology Research in the Interest of Society Jim Demmel, Chief Scientist EECS and Math Depts. www.citris.berkeley.edu.
UC Santa Cruz
Center for Information Technology Research in the Interest of Society
Jim Demmel, Chief Scientist EECS and Math Depts.
www.citris.berkeley.edu
C
enter For
I
nformation
T
echnology
R
esearch In The
I
nterest Of
S
ociety
Major new initiative jointly with UC Berkeley, UC Davis, UC Merced, UC Santa Cruz, LBNL Over 100 faculty from 21 departments Many industrial partners Significant State and private support CITRIS will focus on IT solutions to tough, quality-of-life related problems
3 other such centers: CNSI, CalIT2, QB3
Committed Support Founding Corporate Members of CITRIS
We have received written pledges to CITRIS of over $170 million from individuals and corporations range vision committed to the CITRIS long-
$100 million from State for facilities
Significant Federal funding
Scientific Agenda CITRIS Organization
Outline
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
The CITRIS Model
Core Technologies
• Human-Comp Interaction • Prototype Deployment
Societal-Scale Information Systems (SIS) Foundations
• Reliability • Availability • Security • Algorithms • Social, policy issues
Applications
• IT in service of society • Large impact on California
Technology Invention in a Social Context
:
Quality of Life Impact
Energy Efficiency Disaster Response and Homeland Defense Education
Technology Invention in a Social Context
:
Quality of Life Impact
Transportation Planning Monitoring Health Care Land and Environment
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
Societal-Scale Systems
Secure, non-stop utility Always connected Diverse components Adapts to interfaces/users
“Server” “Client”
Massive Cluster Gigabit Ethernet Clusters
Scalable, Reliable, Secure Services Information Appliances MEMS Sensors
Smart Dust
MEMS-Scale Sensors/Actuators/Communicators
Create a dynamic network of power-aware sensors for
Temperature Humidity Pressure Position Acceleration Light Sound Magnetism Chemicals Biological Agents
Current off-the-shelf design
512 bytes RAM, Radio with 10-100 ft range
TinyOS for programming
February 2000
February 2003
February 2001 August 2001 February 2002
Ad-hoc sensor networks work
29 Palms Marine Base, March 2001
10 Motes dropped from an airplane landed, formed a wireless network, detected passing vehicles, and radioed information back Intel Developers Forum, Aug 2001
800 Motes running TinyOS hidden in auditorium seats started up and formed a wireless network as participants passed them around
tinyos.millennium.berkeley.edu
Smart Dust Goes National
Selected as DARPA networked embedded system tech open platform (NEST) Over 5000 Motes used or shipped to other groups
Academia: UCSD, UCLA, USC, MIT, Rutgers, Dartmouth, U. Illinois UC, NCSA, U. Virginia, U. Washington, Ohio State
Industry: Intel, Crossbow, Bosch, Accenture, Mitre, Xerox PARC, Kestrel
Government: Wright Patterson AFB, NCSC
Ongoing training courses
Micro Flying Insect
Collaboration with Biologist Dickinson
Synthetic Insects
(Smart Dust with Legs) Goal: Make silicon walk.
•Articulated Legs •Size ~ 1-10 mm •Speed ~ 1mm/s
MEMS Technology Roadmap (DARPA) 2010 2004 2005
MEMS Rotary Engine Power System MEMS Single Molecule Detection Systems MEMS Micro Sensor Networks (Smart Dust)
2002 2003
MEMS Immunological Sensors MEMS “Mechanical” Micro Radios
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
What is Disaster Response?
Sensors installed near critical points Sensors measure
Motion (normal deterioration vs serious damage)
Occupancy (where are people?) Fire, heat, chemicals, biological agents
Sensors report location, kinematics of damage during and after an extreme event
Guide emergency personnel Assess structural safety without deconstructing building
Many Scenarios
Seismic Monitoring of Housing • Many such buildings collapsed or were severely damaged in the 1994 Northridge Earthquake.
• Experimental evaluation of a full-scale structure on the Richmond Field Station shake table.
• Part of the CUREe-Caltech Tuck-Under Parking Apartment Building Experiment
Seismic Monitoring of Buildings: Before CITRIS
$8,000 each
Seismic Monitoring of Buildings: With CITRIS Wireless Motes
$70 each
Mote (ADXL202) vs. Traditional Piezo Accelerometer Time Domain Comparison Frequency Domain Comparison
Tokachi Port, Hokkaido
Blast-induced Liquefaction Test
ours theirs theirs theirs ours
400+ Came to Watch
Post-Blast Liquefaction
A commercial product
Crossbow CN4000 Wireless Structural Monitoring System
3D Accelerometer
12 bits of resolution, up to 2G
Temperature
-40 o C to +85 o C, to within
2 o
Wireless communication
1 mile line-of-site range
www.xbow.com
C
Future Disaster Response Work
Golden Gate Bridge
Wind, seismic, security monitoring
Masada
King Herod’s Palace
Seismic (tourist) monitoring
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
The Inelasticity of California’s Electrical Supply
800 700 600 500 400 300 200 100 0 20000 25000 30000 35000 40000 45000 MW
Power-exchange market price for electricity versus load (California, Summer 2000)
How to Address the Inelasticity of the Supply
Reduce demand, or spread demand over time
Make cost of energy
visible to end-user function of load curve
“Real-time pricing”
Phase 1: Expose energy usage to user; helps eliminate waste
Phase 2: Expose real-time prices to user Phase 3: Automatic control to optimize price, safety, user comfort, other economic goals
Improve efficiency of generation and distribution network (supply side)
Enabled by Information!
Cory Hall Energy Monitoring Network
50 nodes on 4 th floor
30 sec sampling
250K samples to database over 6 weeks
Moved to Intel Lab – come play!
Control of HVAC systems
Simulation results – assuming multiple sensors
Hot August day in Sacramento
Underfloor HVAC saves 46% of energy
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
Habitat Monitoring on Great Duck Island
Enable researchers anywhere in the world to engage in non-intrusive monitoring of sensitive wildlife and habitats Study breeding cycle of Leach's Storm Petrel
Duck Island System Architecture
Duck Island Sample Data
Light, Temperature, Infrared, Humidity, Power
Live data at www.greatduckisland.net
Monitoring Mogau Caves, China
Location of ancient cave paintings
Goal: monitor humidity, other factors that could damage paintings
Supported by
Dunhuang University
Osaka University, Dept of Global Architecture
Getty Foundation
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks
Recent progress in large scale applications Disaster Response Energy Efficiency Environmental Monitoring Education New Application Areas High Level Building Blocks
Education Goals
UC Merced curriculum collaboration
New UC campus to open
Tele-laboratories and smart classrooms
Mechanical Rapid-Prototyping, MEMS, Microlab, Robotics
Masters degrees for professionals
New graduate courses
Discussions with Chinese Ministry of Education
UC Merced (1)
New campus to open in 2004
Help accommodate 50% growth in UC
Goal: “Export” Berkeley’s curriculum to Merced
Start with programming courses
Not “Distance Learning”: Still need local instructors
Replaces lectures by directed on-line student team work
Instructor monitors teams, gives short directed lectures
Student Portal
Reading, problem solving, discussion, quizzes
Course Builder and Customizer for faculty
Course database to support upgrading and customizing
UC Merced (2)
Summer 2002 at Berkeley
CS3 (Introduction to Symbolic Computing for Non Majors)
Results: better exam results, high ratings Fall 2002 at Berkeley
CS3 again, self-paced too
Spring 2003 at Merced Community College
Local instructor, Support from Berkeley staff
2004
Main Merced campus to open Other courses available
Masters Degrees for Professionals
Management of Technology (MOT)
High performance Communication Networks
Wireless Systems
Embedded Computing
MEMS
Internet-based Design, Manufacturing, and Commerce
Management of Technology (MOT)
ME221
High Tech Product Design and Rapid Manufacturing
Taught in campus TV studio
Webcast to Intel, Sony and NEC
12 off-campus students, many more on campus
Designed products
Sent files to Berkeley’s CyberCut/CyberBuild system
Custom, Internet-based manufacturing
See mot.berkeley.edu
Summit
ME221 Project Examples
!ntro
bentoBox
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks Recent progress in large scale applications
New Application Areas Electronic Cultural Atlas Initiative (ECAI) Berkeley Laboratory in Experimental Economics (XLAB) High Level Building Blocks
Electronic Cultural Atlas Initiative (ECAI)
Collaborative project which combines global mapping, imagery, and texts
TimeMap to view events, artifacts, images by time and place
Headquartered at Berkeley (Lancaster, Chinese Studies)
A few sample projects (from 300)
Time Map Korea
Silk Road Atlas
South Asian Animation
Great Britain Historical GIS
See www.ecai.org
Electronic Cultural Atlas Initiative (ECAI)
Proposed CITRIS Collaboration:
Authoring tools tailored to the needs of specific disciplines for course development
Use of standards for documentation
Training programs for the use of the tools and the development of documentation
ECAI pilot group focused on Chinese studies
history
art history
language study
Need for servers
Berkeley Laboratory in Experimental Economics (XLAB)
Auerbach, Gilbert, Akerlof (Nobel Prize 2001)
Joint between Economics and Business School
Experimental Economics becoming major methodology
Experimentally evaluate economic assumptions, theories
How real people make economic decisions
Why do some products succeed, others not?
Need servers
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks Recent progress in large scale applications New Application Areas
High Level Building Blocks Scope Project descriptions
Societal-Scale Information System SIS Massive Cluster Gigabit Ethernet Clusters
“Server” “Client” Scalable, Reliable, Secure Services Information Appliances MEMS Sensors
Desirable SIS Features Problems to solve
• Integrates diverse components seamlessly • Easy to build new services from existing ones • Adapts to interfaces/users • Non-stop, always connected • Secure
Outline – Scientific Agenda
Scientific Agenda Overview Low Level Hardware and Software Building Blocks Recent progress in large scale applications New Application Areas
High Level Building Blocks Scope (A few) Project descriptions
Projects
ROC (Recovery Oriented Computing)
Patterson, Fox (Stanford)
Oceanstore and Tapestry
Kubiatowicz, Joseph
OSQ (Open Source Quality)
Aiken, Henzinger, Necula
High Productivity Software
Yelick, Demmel
Recovery Oriented Computing (ROC)
Dave Patterson and a cast of 1000s:
Aaron Brown, Pete Broadwell, George Candea † ,Mike Chen, James Cutler † , Patricia Enriquez*, Prof. Armando Fox † , Emre Kıcıman † , Matthew Merzbacher*, David Oppenheimer, Naveen Sastry, William Tetzlaff, Jonathan Traupman, and Noah Treuhaft U.C. Berkeley, *Mills College, †
Stanford University
October 2002
Learning from others: Bridges 1800s: 1/4 iron truss railroad bridges failed!
Safety is now part of Civil Engineering DNA Techniques invented since 1800s:
1.
2.
Learn from failures vs. successes Redundancy to survive some failures 3.
Margin of safety 3X-6X vs. calculated load To hide errors in building material, construction, design, and use What is CS&E version of safety margin?
Margin of Safety in CS&E?
Like Civil Engineering, never make dependable systems until add margin of safety (“margin of ignorance”) for what we don’t (can’t) know?
Today: design to tolerate expected (HW) faults
RAID 5 Story
Operator removing good disk vs. bad disk
Temperature, vibration causing failure before predicted on data sheets
CS&E Margin of Safety: Tolerate human error in design, in construction, and in use?
Perhaps we need to “over engineer” to deliver what people expect
Recovery-Oriented Computing Philosophy
“If a problem has no solution, it may not be a problem, but a fact, not to be solved, but to be coped with over time”
— Shimon Peres (“Peres’s Law”)
People/HW/SW failures are facts, not problems
Recovery/repair is how we cope with them
Improving recovery/repair improves availability
UnAvailability = MTTR MTTF
(assuming MTTR much less than MTTF)
1/10th MTTR just as valuable as 10X MTBF
ROC also helps with maintenance/TCO
since major Sys Admin job is recovery after failure
MTTR more valuable than MTTF?
Threshold => non-linear return on improvement if recovery time drops below threshold
8 to 11 second abandonment threshold on Internet
30 second NSF client/server threshold
Ebay 4 hour outage, 1 st major outage in year
More people in single event worse for reputation?
One 4-hour outage/year => NY Times => stock?
250 people in a single plane is front page news; 1 person per day in a planes is not news, even though more die per year in general aviation than in commercial
MTTF normally predicted vs. observed
Include environmental error operator error, app bug?
Much easier to verify MTTR than MTTF!
1.
2.
3.
4.
5.
Five “ROC Solid” Principles
Given errors occur, design to recover rapidly Extensive sanity checks during operation
To discover failures quickly (and to help debug) Report to operator (and remotely to developers) Tools to help operator find, fix problems
Since operator part of recovery; e.g., hot swap; undo; graceful, gradual SW upgrade/degrade Any error message in HW or SW can be routinely invoked, scripted for regression test
To test emergency routines during development
To validate emergency routines in field To train operators in field Recovery benchmarks to measure progress
Recreate performance benchmark competition
Projects
ROC (Recovery Oriented Computing)
Patterson, Fox (Stanford)
Oceanstore and Tapestry
Kubiatowicz, Joseph
OSQ (Open Source Quality)
Aiken, Henzinger, Necula
High Productivity Software
Yelick, Demmel
OceanStore
Global-Scale Persistent Storage
OceanStore Context: Ubiquitous Computing
Computing everywhere:
Desktop, Laptop, Palmtop
Cars, Cellphones
Shoes? Clothing? Walls?
Connectivity everywhere:
Rapid growth of bandwidth in the interior of the net
Broadband to the home and office
Wireless technologies such as CMDA, Satelite, laser
Questions about information:
Where is persistent information stored?
Want: Geographic independence for availability, durability, and freedom to adapt to circumstances
How is it protected?
Want: Encryption for privacy, signatures for authenticity, and Byzantine commitment for integrity
Can we make it indestructible?
Want: Redundancy with continuous repair and redistribution for long-term durability
Is it hard to manage?
Want: automatic optimization, diagnosis and repair
Who owns the aggregate resouces?
Want: Utility Infrastructure!
Utility-based Infrastructure
Canadian OceanStore
Sprint
AT&T Pac Bell IBM IBM
Transparent data service provided by federation of companies:
Monthly fee paid to one service provider
Companies buy and sell capacity from each other
OceanStore Assumptions
Untrusted Infrastructure:
The OceanStore is comprised of untrusted components Only ciphertext within the infrastructure Responsible Party:
Some organization (i.e. service provider) guarantees that your data is consistent and durable Not trusted with content of data, merely its integrity Mostly Well-Connected:
Data producers and consumers are connected to a high-bandwidth network most of the time Exploit multicast for quicker consistency when possible Promiscuous Caching:
Data may be cached anywhere, anytime Optimistic Concurrency via Conflict Resolution:
Avoid locking in the wide area
Applications use object-based interface for updates
First Implementation [Java]:
Event-driven state-machine model Included Components
Initial floating replica design
Conflict resolution and Byzantine agreement Routing facility (Tapestry)
Bloom Filter location algorithm Plaxton-based locate and route data structures Introspective gathering of tacit info and adaptation
Language for introspective handler construction Clustering, prefetching, adaptation of network routing Initial archival facilities
Interleaved Reed-Solomon codes for fragmentation Methods for signing and validating fragments Target Applications
Unix file-system interface under Linux (“legacy apps”) Email application, proxy for web caches, streaming multimedia applications
OceanStore Conclusions
OceanStore: everyone’s data, one big utility
Global Utility model for persistent data storage OceanStore assumptions:
Untrusted infrastructure with a responsible party Mostly connected with conflict resolution Continuous on-line optimization
OceanStore properties:
Provides security, privacy, and integrity
Provides extreme durability
Lower maintenance cost through redundancy, continuous adaptation, self-diagnosis and repair
Large scale system has good statistical properties
Oceanstore Prototype Running with 5 other sites worldwide
Projects
ROC (Recovery Oriented Computing)
Patterson, Fox (Stanford)
Oceanstore and Tapestry
Kubiatowicz, Joseph
OSQ (Open Source Quality)
Aiken, Henzinger, Necula
High Productivity Software
Yelick, Demmel
OSQ: Open Source Quality
Goals: Automatic analysis of software for
Finding bugs
Checking specifications
Of a at least simple properties
Help with writing specifications
Focus
Large, ubiquitous systems programs
Linux kernel, sendmail, apache, etc.
Tools
CCured
Automatically enforce memory safety for C
Array index out of bounds, wild pointer dereferences CQual
Specification and checking of system-specific properties
Locking, file handling, ordering of method calls, … CHIC and MOCHA
Interface compatibility checking
Automatic verification of interface protocols BLAST
Software model checker
E.g., for checking complex control-flow in device drivers www.cs.berkeley.edu/~weimer/osq
Ccured - Type-Safe programming in C
Memory safety
“must have” property for reliability and security (50% of reported vulnerabilities are due to buffer overruns) C was designed to be flexible not safe!
But most C programs use dangerous C features benignly CCured
Analyzes the program statically to find benign pointer use Inserts run-time checks where static analysis fails Run-time overhead of 50% (unlike 10x for Purify) Prototype works for large programs
Sendmail, bind, openssl, SpiderMonkey engine, Apache modules
Requires some intervention (similar to porting) See http://www.cs.berkeley.edu/~necula/ccured
CQual: Extending Standard Types
Problem: Many unchecked properties
Is the lock acquired?
Is the file open?
CQual checks such properties for C programs
Idea: User-defined type qualifiers
const int
Distribution available
Found many bugs in device drivers Found many security vulnerabilities
CHIC and MOCHA Interface Compatibility Checking
Objective: Automatic verification of compatibility between interface protocols of hardware and software components Approach: -
Interface protocols
expose more information than data types The interface protocol of a file server may specify that the
read-file
method cannot be called before the
open-file
method has been called.
The interface protocol of a bidirectional bus may specify that no two clients can write to the bus at the same time.
-Verifying interface protocol compatibility lies in difficulty between type checking and full behavioral verification
Interface Compatibility Checking
Tools: For software interfaces: CHIC (extension of Jbuilder) For hardware interfaces: MOCHA Applications: Software interfaces: TinyOS (an OS for adhoc networking) Hardware interfaces: PCI bus and clients Future Plans: -Check conformance of implementation with interface -Interface protocols with real-time and resource constraints
Projects
ROC (Recovery Oriented Computing)
Patterson, Fox (Stanford)
Oceanstore and Tapestry
Kubiatowicz, Joseph
OSQ (Open Source Quality)
Aiken, Henzinger, Necula
High Productivity Software
Yelick, Demmel
Tools for High Productivity Computing Kathy Yelick U.C. Berkeley
http://www.cs.berkeley.edu/~yelick/
HPC Problems and Approaches
Parallel machines are too hard to program
Users “left behind” with each new major generation Efficiency is too low
Even after a large programming effort
Single digit efficiency numbers are common Even on sequential machines Approach
Titanium:
Modern (Java-based) language that provides performance transparency Kathy Yelick, Susan Graham, Paul Hilfinger, Phil Colella Bebop: Berkeley Benchmarking and Optimization group
Kathy Yelick, Jim Demmel Unified Parallel C (UPC)
Global address space language based on C Commercial support (HP, Cray,…)
Global Address Space Programming
Intermediate point between message passing and shared memory
Program consists of a collection of processes.
Fixed at program startup time, like MPI
Local and shared data, as in shared memory model
But, shared data is partitioned over local processes
Remote data stays remote on distributed memory machines
Processes communicate by reads/writes to shared variables
Note: These are not data-parallel languages
Heroic compilers not required
Examples are UPC, Titanium, CAF, Split-C
http://upc.nersc.gov
http://titanium.berkeley.edu/
Titanium Overview
Object-oriented language based on Java with:
Scalable parallelism
SPMD model with global address space
Multidimensional arrays
points and index sets as first-class values
Immutable classes
user-definable non-reference types for performance
Operator overloading
by demand from our user community
Semi-automated memory management
uses memory regions for high performance
Serial Java Performance
Performance on a Sun Ultra 4
70 60 50 40 30 20 10 0 Overall FFT SOR MC Java C Ti Ti -nobc Sparse LU
Serial Java Performance
Pentium 4, 1.45 GHz SciMark Performance on Pentium 4 (1.5GHz)
450 400 350 300 250 200 150 100 50 0 Overall java FFT SOR C (gcc -O6) MonteC Ti -O Sparse Ti -O -nobcheck LU
Heart Simulation
Problem: compute blood flow in the heart
Modeled as elastic structure in incompressible fluid
The “immersed boundary method” [Peskin and McQueen].
20 years of development in model
Possible applications in the design of artificial heart valves
Implemented as a general tool for fluid flow with elastic structures
Written in Titanium
Use Java features for extensibility
Applied to heart, inner ear
Parallel implementation for shared/distributed memory
Image from PSC
AMR Gas Dynamics
Adaptive mesh refinement (AMR)
Places more computation where there is more activity
Uses tree of block-structured meshes Gas Dynamics code in AMR
Developed by McCorquodale and Colella 3D supported 2D example: Mach-10 shock on solid surface at oblique angle
Summary
Global address space languages offer alternative to MPI for large machines
Easier to use: shared data structures
Recover users left behind on shared memory?
Performance tuning still possible
Implementation
Small compiler effort given lightweight communication
Portable communication layer: GASNet Difficulty with small message performance on IBM SP platform
Context: High-Performance Libraries
Application performance dominated by a few
computational kernels
Today: Kernels hand-tuned by vendor or user
Performance tuning challenges
Performance is a complicated function of kernel, architecture, compiler, and workload Tedious and time-consuming
Successful automated approaches
Dense linear algebra: PHiPAC, ATLAS Signal processing: FFTW, SPIRAL, UHFFT
Tuning pays off – ATLAS
Extends applicability of PHIPAC; Incorporated in Matlab (with rest of LAPACK)
Tuning Sparse Matrix Kernels
Optimizations depend on
Machine characteristics (as in dense case) Nonzero pattern in the sparse matrix Performance tuning issues in sparse linear algebra
Indirect, irregular memory references High bandwidth requirements, poor instruction mix Performance depends on architecture, kernel, and matrix How to select data structures and implementations at run-time Typical performance: < 10% machine peak Our approach to automatic tuning: for each kernel,
Identify and generate a space of implementations
Search the space to find the fastest one (models, experiments)
Machine Profiles Computed Offline
Register blocking performance for a dense matrix in sparse format.
333 MHz Sun Ultra 2i 73 105 500 MHz Intel Pentium III 35 375 MHz IBM Power3 172 42 250 800 MHz Intel Itanium 88 110
Register Blocked SpMV Performance: Ultra 2i
(See upcoming SC’02 paper for a detailed analysis.)
Bebop Summary
Bebop project applying these techniques and other optimizations to a number of sparse matrix kernels Further performance improvements to sparse-matrix-vector multiply
Symmetry (up to 1.5 – 2x speedups) Diagonals, block diagonals, bands (1.2 – 2x) Splitting for variable structure (1.3 – 1.7x) Reordering to create dense structure (1.7 x) Cache blocking (1.5 – 4x) Multiple vectors (2 – 7x) And combinations … How to choose optimizations and tuning parameters Sparse triangular solve (1.2 – 1.8x) Higher level Kernels
y=A T
A*x, y=AA
T *x (up to 3x)
Powers (y=A
k
*x), sparse triple-product (R*A*R
T
), … (future work)
More Projects …
Millennium and PlanetLab
Culler, Kubiatowicz, Stoica, Shenker
www.planet-lab.org/ www.millennium.berkeley.edu/ Sahara
S
ervice
A
rchitecture for
H
eterogeneous
A
ccess,
R
esources, and
A
pplications Katz, Joseph, Stoica sahara.cs.Berkeley.edu/ Security
Wagner, Tygar Visualization
Hamann, Joy, Max, Staadt CAD for MEMS
Demmel, Govindjee, Agogino, Pister, Bai
www-bsac.EECS.Berkeley.EDU/cadtools/sugar/sugar/
Scientific Agenda CITRIS Organization
Outline
Institute Governing Board
See Detail Listing in Table Attached
UCB Chancellor
Robert M. Berdahl
Director
Ruzena Bajcsy
Institute Advisory Board
See Detail Listing in Table Attached
Chief Scientist & Associate Director
James Demmel
Education Coordination Council
Paul Wright, Chair, UCB -Alice Agogino UCB, -Jeff Wright UCM, Pat Mantey UCSC, -Harry Matthews UCD, Linkage to UC Extension Industrial Representatives Linkage to CITRIS Research Projects Inter-Campus Relations Industrial Relations/Tech Transfer Communications: Web & Public Relations Linkage to Regents & State
Administrative
Administrative Staff Contracts & Grants
Director
Albert Pisano Links to Berkeley, Davis & Santa Cruz Offices of Sponsored Research
Research Coordination Council
G. Fenves* D. Culler* S. J. B. Yoo* D. Patterson*
Driving Engineering Infra- Foundations Applications Systems structure Technologies
Smart Classrooms
A. Joseph, J. Canny, P. Mantey
Smart Buildings
E. Arens
Disaster Risk Reduction
S. Glaser
Transportation Networks
P. Varaiya
Environmental Monitoring
D. Niemeier
Medical Alert Networks
T. Budinger
Distributed System
Architectures
R. Katz D. Long
mechanics
Computing
J. Canny B. Hamann
Microelectronics & Microelectro-
R. Howe, B. Yoo, C. Gu, T.J. King
Human - Centered System Reliability
T Henzinger
System Availability & Maintainability
D. Patterson
Security, Privacy & Policy
H. Varian S. Sastry
Algorithmic
Foundations
C. Papdimitriou J. Demmel * Co-Chairs appointed from faculty below; Computer Support serve on rotating basis. Sections in blue Multicampus make up the Faculty Executive Committee.
Current and Near Term Space
Intel Lab in Power Bar Building on Shattuck
Hearst Mining (Early 2003)
BID (Berkeley Institute of Design)
The New CITRIS Building
Construction will begin in summer 2003
Architectural plans are well underway
It will house the Microfabrication Laboratory
Remaining space will be allocated to other CITRIS related projects
Including Corporate Visitors
CITRIS-Affiliated Research Activities
Berkeley Sensor and Actuator Center (BSAC) (14 faculty, 100 students)
Designs sensors and actuators
Microfabrication Laboratory (71 faculty, 254 students)
Fabricates chips
Berkeley Wireless Research Center (BWRC) (16 faculty, 114 students)
Designs low-power wireless devices.
International Computer Science Institute (ICSI) (5 faculty, 18 students)
Networking, speech, human centered computing
Millennium Project (15 faculty)
~1000 processors in campus-wide parallel computing facility
Gigascale Silicon Research Center (GSRC) (23 faculty, 60 students)
Design tools for sub-micron silicon technology
CITRIS-Affiliated Research Activities
(continued)
Center for Hybrid Embedded Systems Software (CHESS)
New $13M NSF Center
Berkeley Institute of Design (BID) (10 faculty)
New center to study design of SW, products, living spaces EECS, ME, Haas, SIMS, IEOR, CDV, CED, Art Practice
Center for Image Processing and Integrated Computing (CIPIC) (8 faculty, 50 students) (UCD)
Large scale data visualization
Applications-Related Current Activities
Partners for Advanced Transit and Highways, PATH (20 faculty, 70 students; UC, Caltrans, other universities)
Technology to improve transportation in California
Pacific Earthquake Engineering Research Center, PEER ( 25 faculty, 15 students; 9 universities),
Identify and reduce earthquake risks
Berkeley Seismological Laboratory (15 faculty, 14 students)
Runs a regional seismological monitoring system
Studies, provides earthquake data to governments
.
National Center of Excellence in Aviation Operations Research, NEXTOR (6 faculty, 12 students),
Studies complex airport and air traffic systems.
Applications-Related Current Activities
(continued)
Center for the Built Environment (CBE) (19 faculty/staff)
New building technologies and design techniques
Lawrence Berkeley National Laboratory (LBNL)
National Energy Research Supercomputing Center (NERSC)
Supercomputer Center
Environmental Energy Technologies (EET)
Better energy-saving technologies, reduced environmental impact
Future Steps
Build testbeds Training of students Deepen interaction with industrial and government partners
Intellectual Property Put the social into CITRIS Write proposals…
CITRIS Web site:
www.citris.berkeley.edu
This talk:
www.cs.berkeley/~demmel /CITRIS_Overview_Feb03.ppt/