# Presentation: 070481

## Toward Petascale ComputingPERCS: IBM Effort under HPCS

- Mootaz Elnozahy
- IBM

## Overview

- Constraints
- Vision
- Panel questions
- Conclusion
*I am not going to say something you don’t know*

## Constraints

- Legacy investments
- HPC customer diversity
- Economic factors *cannot be ignored*
- Remember the shift to COTS in the 90’s!!!
- Business model for IBM
- Must do well both on commercial and scientific workloads
- Cost issues
- Threat of commoditization
- Productivity is a key problem
- Petascale?

## IBM’s Vision

**A dynamic system that adapts to application needs**

- The strategy
** ****Aggressive productivity targets**
** ****Commercial viability**

## It’s the Software, Baby!

**Adaptability is key**
- Architecture gets closer to application needs, yielding better performance and broader application range
**Backward compatibility with PowerPC**
- Leverages existing infrastructure, training and investment
- Exploits proven ability of the current architecture to perform well for *many *apps
**Leverage open source**
**Modular design packaged in different configurations**

## Architecture Innovations

**Adaptation**
- Vector/stream processor morphs
- Memory-in-processor morph
- SMT and conventional caches for commercial apps
**Proactive memory architecture**
- Embedding intelligence across memory hierarchy
**Leverage technology advantages**
- Aggressive hardware design
- New revolutionary packaging and device technologies subject to practicality & cost

## Panel Questions (1-2)

- What architectural features will be easy to exploit and yield good performance?
- Reconfiguration of the processing resources to match the need of the applications
- What anticipated features will be complex and problematic for language designers, compiler writers and applications programmers alike?
- Management of memory, on chip, on main banks, and on disks

## Panel Questions (3)

- What "features" will be so complex that only the run-time environment should see them, and could lead to fragile or down right awful performance?
- Ability to use and manage binary rewriting to improve performance using feedback from system monitoring hardware.

## Panel Questions (4)

- Will architectures have so much complexity, and require so many levels of parallelism ...
- Yes.
- Shared memory abstraction in processor thru multithreading
- Shared memory abstraction on SOC through multi-core chip
- Shared memory abstraction on SMP interconnect (bus)
- Shared memory abstraction on NUMA interconnect
- Message passing
- Yeah... right...
- ...that our programming models need to reflect this same complexity?
- Simplicity must win
- Some level of complexity will creep upward to at least reflect a scalable hardware model that could yield good scaling for applications.

## Panel Questions (5-6)

- What are the trends?
- The trends are more toward commodity-based systems.
- Dell model may kill "interesting" architectures (software or hardware)
- What will be the key things that programming models need to address?
- The scalability of the system. Without this, petascale computing will not happen.

## Summary

**An ambitious vision for petascale computing by adapting systems to applications **
**Explore technologies otherwise deemed too risky**
**Increase application base for economic viability**
**Petascale computing is possible in hardware, but software progress is more critical**
**Focus on software and productivity**
**These problems are being researched under the PERCS/HPCS project at IBM**

## Mootaz’s Views on Bill’s Views

- MPI is bad?
- Yes, but what about all the code that is there?
- Traditional path is not going to give you performance
- I agree, but ignore it at your peril 
- IBM wants a check
- You bet!!! 
- But at least, we are maintaining a strong research program—give us some credit (and $’s)
- Bill position: My architecture is best
- But what about software?