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Garden of Architectures CSG Workshop May 2008

Garden of Architectures CSG Workshop May 2008. Jim Pepin CTO. Disruptive change . Doubling (Moore’s Law or …) Transistors Multi-core Disk capacity New mass storage (flash, etc) Parallel apps Storage mgmt Optics based networking. Disruptive Change. Federated identity Large V/O

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Garden of Architectures CSG Workshop May 2008

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  1. Garden of ArchitecturesCSG WorkshopMay 2008 Jim Pepin CTO

  2. Disruptive change • Doubling (Moore’s Law or …) • Transistors • Multi-core • Disk capacity • New mass storage (flash, etc) • Parallel apps • Storage mgmt • Optics based networking

  3. Disruptive Change • Federated identity • Large V/O • Shared research/clinical spaces • Team science/academics • Paradigm shift • CI as a tool for all scholarship

  4. Disruptive Change • Lack of diversity in computing architectures • X64 has ‘won’ • Maybe IBM/Power exists at edges • Maybe Sun/SPARC at edges • This creates mono-culture • Dangerous • Innovation here in consumer space • Game boxes/phones drive here

  5. Network Futures • Optical Bypasses • Very high speed • Low friction • Low jitter • Facilities based • GLIF examples • RONs • Exchanges

  6. Network Futures • “Security” is driving researchers away from us • Are we the problem? • Where does ‘security’ belong? • How do we do VOs with two port internet? • Will we see our networks become ‘campus phone switch’ of the 2010s

  7. Data futures • Massive storage (really really big) • Object oriented (in some cases) • Preservation • Provenance • Distributed • Blur between data bases/file systems • Meta data

  8. New Operating Environments • Operating systems in network • Grids • ID management • But done poorly from integration view • How to build petascale single systems • Scaling applications is biggest problem • Training • “Cargo Cult” systems and applications

  9. New Operating Environments • 100s of TF at campus (but how to use it and build it on campus) • Tied into national petascale systems • All the problems on terragrid and VOs on steroids. • Network security friction points • Identity management • Non-homogenous operating environments

  10. Computation • Massively parallel • Many cores (doubling every 2-3 yrs) • Commodity parts • Massive collections of nodes with high speed interconnect • Heat and power density • Optical on chip technology • Legacy code scales performs poorly (or worse)

  11. Viz/remote access • SHDTV like quality (4k) • Enables true telemedicine and robotic surgery • Massive storage ties to this • Optiputer project is example (CALIT2) • Colab spaces with true haptic and visual presence. • Social sites are simple prototypes • Large screen applications and tele-presence

  12. Versus • Old Code • Much based on 360/VAX/Name it • Gaussian poster child • Vector optimized • Static IT models • Network defenders in IT hurt researchers • Researchers don’t play with others well • Condo model evolving

  13. Versus • Thinking this is just for science/engineer • Large data • Interactive applications • Social Science apps • Education outcomes at Clemson • Large data, statistics on huge scale • Shoah Foundation at USC • Massive data, networks, VO

  14. Vision/Sales Pitch • Access to various kinds of resources • Parallel high performance • Can be in condo (depends on politics) • Flexible node configurations • Large storage of various flavors • Viz • Leading edge networks

  15. “Clusters” • Large collection of multi-core • High performance interconnect • What makes cluster not just a bunch of nodes • Access to large data storage at parallel speeds • Lustre • SAM/QFS • PVFS • Ability to put in large memory nodes

  16. “Clusters” • Magic chips • GPUs, FPGAs etc • Botique today but gains can be enormous • Relation to desktops/local systems • How to integrate into national systems • Identity/security/networking • Viz clusters • Render agents • Large scale, friction free networking

  17. Storage Farms • Diverse data models • Large streams (easy to do) • Large number of small files (hard to do) • Integrate mandates (security, preservation) • Blur between institution data and personal/research • Storage spans external, campus, departmental,local • Speed of light matters

  18. Meaning of Life • Much closer relations needed to central IT • Networks/identity mgmt/security/policy • But not just ‘at scale’ • How to use the disruptive technologies • Core,GPUs,Cell,FPGA,Flash,optical networks • Disruptive software/services as well

  19. Meaning of Life • Build ecosystem of services • Some central, some local, some external • Not just computing, networks and storage • Our community has “gone global” • The campus is not a castle. • Earlier example of 8 social science faculty • We have thousands of communities • Can’t be one size fits all

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