UCSD SAN DIEGO SUPERCOMPUTER CENTER 1 Who needs a supercomputer? Professor Snavely, University of California Professor Allan Snavely University of California, San Diego and San Diego Supercomputer Center

Performance Modeling and Characterization Lab PMaC Arent computers fast enough already? This talk argues computers are not fast enough already Nor do supercomputers just naturally get faster as a result of Moores Law. We explore implications of: Moores Law Amdahls Law Einsteins Law Supercomputers are of strategic importance, enabling a Third Way of doing science-by-simulation Example: Terashake Earthquake simulation Viable National Cyberinfrastructure requires centralized supercomputers Supercomputing in Japan, Europe, India, China Why + Moores Law does not solve all our problems

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC The basic components of a computer Your laptop has these:

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Supercomputers (citius, altius, fortius) Supercomputers are just faster, higher, stronger, than your laptop, more and faster processors etc. capable of solving large scientific calculations

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC An army of ants approach In Supercomputers such as Blue Gene, DataStar, thousands of CPUs cooperate to solve scientific calculations

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Computers live a billion seconds to our every one! Definitions: Latency is distance measured in time Bandwidth is volume per unit of time Thus, in their own sense of time, the latencies and bandwdiths across the machine room span 11 orders of magnitude! (from Nanoseconds to Minutes.) To a supercomputer, getting data from disk is like sending a rocket- ship to Saturn!

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Moores Law Gordon Moore (co-founder of Intel) predicted in 1965 that the transistor density of semiconductor chips would double roughly every 18 months. Moores law has had a decidedly mixed impact, creating new opportunities to tap into exponentially increasing computing power while raising fundamental challenges as to how to harness it effectively. Things Moore never said: computers double in speed every 18 months cost of computing is halved every 18 months cpu utilization is halved every 18 months

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Moores Law Moores Law: the number of transistors per processor chip by doubles every 18 months.

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Snavelys Top500 Laptop? Among other startling implications of Moores Law is the fact that the peak performance of the typical laptop would have placed it as one of the 500 fastest computers in the world as recently as Shouldnt I just go find another job now? No, because Moores Law has several more subtle implications and these have raised a series of challenges to utilizing the apparently ever-increasing availability of compute power; these implications must be understood to see where we are today in High Performance superComputing (HPC).

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC The Vonn Neumann bottleneck Scientific calculations involve operations upon large amounts of data, and it is in moving data around within the computer that the trouble begins. As a very simple pedagogical example consider the expression A + B = C The computer has to load A and B, + them together, and store C + is fast by Moores Law, load and store is slow by Einsteins Law

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Supercomputer Red Shift While the absolute speed of all computer subcomponents have been changing rapidly, they have not all been changing at the same rate. While CPUs get faster they spend more time sitting around waiting for data

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Amdahls Law The law of diminishing returns When a task has multiple parts, after you speed up one part a lot, the other parts come to dominate the total time An example from cycling: On a hilly closed-loop course you cannot ever average more than 2x your uphill speed even if you go downhill at the speed of light! For supercomputers this means even though processors get faster the overall time to solution is limited by memory and interconnect speeds (moving the data around)

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Red Shift and the Red Queen It takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that! Corollary: Allans laptop is not a balanced system! System utilization is cut in half every 18 months? Fundamental R&D in latency hiding, high bandwidth network, Computer Architecture

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC 3 ways of science Experiment Theory Simulation

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Major Earthquakes on the San Andreas Fault, 1680-present 1906 M M 7.7 The SCEC TeraShake simulation is a result of immense effort from the Geoscience community for over 10 years Focus is on understanding big earthquakes and how they will impact sediment- filled basins. Simulation combines massive amounts of data, high-resolution models, large-scale supercomputer runs TeraShake results provide new information enabling better Estimation of seismic risk Emergency preparation, response and planning Design of next generation of earthquake-resistant structures Such simulations provide potentially immense benefits in saving both many lives and billions in economic losses ? How Dangerous is the Southern San Andreas Fault?

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC TeraShake Animation

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Compute (more FLOPS) Data (more BYTES) Home, Lab, Campus, Desktop Traditional HPC environment Data-oriented Science and Engineering Environment SDSC and Data Intensive Computing Brain mapping TeraShake

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC The Japanese Earth Simulator Took U.S. HPC Community by surprise in 2002 – Computenik For 2 years had more flops capacity than top 5 U.S. systems Approach based on specialized HPC design Still has more data moving capacity Sparked space race in HPC, Blue Gene surpassed for flops 2005

San Diego Supercomputer Center Performance Modeling and Characterization Lab PMaC Summary Red Shift means the promise implied by Moores Law is largely unrealized for scientific simulation that by necessity operate on large data Consider The Butterfly Effect Supercomputer Architecture is a hot field Challenges from Japan, Europe, India, China Large centralized, specialized compute engines are a vital national strategic resources Grids, utility programing, etc. do not meet all the needs of largescale scientific simulation for reason that should now be Consider a galactic scale