One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained...
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Transcript of One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained...
![Page 1: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/1.jpg)
One step ahead
![Page 2: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/2.jpg)
The Challenges of Architectures that Grow to
Petascale and can be Sustained Economically
Steve Reinhardt
Principal Engineer, SGI
spr at sgi.com
![Page 3: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/3.jpg)
SGI’s systems are evolving to enable ultrascale versions of today’s
applications and enable a new type of computational science, while remaining
economically sustainable.
![Page 4: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/4.jpg)
Agenda
• Besides Architecture…• Enabling Ultra-scale Applications• Enabling New Computational Science• Sustaining Economically
![Page 5: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/5.jpg)
Besides Hardware Architecture ...
• Efficient execution environment• RAS • OS architecture
– Linux scaled aggressively, with multiples in ultrascale configurations
• Robust scheduling• RAS • Packaging density / heat dissipation• RAS
![Page 6: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/6.jpg)
Agenda
• Besides Architecture…• Enabling Ultra-scale Applications• Enabling New Computational Science• Sustaining Economically
![Page 7: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/7.jpg)
Local Performance:Needed Flexibility of Memory Access
Note: Original (Jan2003) models used for both X1 and Altix
0.1
1
10
100
cache stride1 gather/scatter
Ban
dwid
th (G
B/s
)
X1
Altix
Price Performance
0.01
0.10
1.00
10.00
cache stride1 gather/scatter
Cos
t of B
andw
idth
(MB
/s p
er $
)
X1
Altix
Absolute Performance
Driven by focus of engineering team
Driven by cost of large engineering team
Driven by parts replication cost
![Page 8: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/8.jpg)
Ideal Machine (Technical/Economic Balance)
Price PerformanceAbsolute Performance
• High, cost-effective cache bandwidth of mass market parts• Highest cost-effective memory bandwidth• Design focus on gather/scatter
0.1
1
10
100
cache stride1 gather/scatter
Ban
dwid
th (G
B/s
)
X1
Altix
ideal
0.01
0.10
1.00
10.00
cache stride1 gather/scatter
Co
st o
f B
and
wid
th (
MB
/s p
er $
)
X1
Altix
ideal
Note: For O(100KP) petascale machines, value of O(5X) processor performance advantage is less than today
![Page 9: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/9.jpg)
Local Performance: Multi-Paradigm
Low Data locality High
Lo
w
Co
mp
ute
h
igh
Inte
ns
ity
Vector-like
PIM-like
Scalar
Application-specific
![Page 10: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/10.jpg)
Ultraviolet : Concept Architecture
MPUMPU MPU
UV Petascale GAM
. Globally Addressable . Low Latency . High Bandwidth . O(100K) Ports
GPUI/O
APU
![Page 11: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/11.jpg)
Global Performance
• Communications– grids becoming more dynamic -> low latency essential – processor counts growing -> low latency essential– low latency -> global address space– in clock periods, remote memory getting further away– bandwidth-conserving operations needed– high absolute link performance
• Synchronization– current mechanisms insufficient for ultrascale– optimizations will help, but maybe not enough– new mechanisms needed
• Dynamic load balancing– mechanisms need to mature, and interfaces become standard
![Page 12: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/12.jpg)
Challenges
• Clear virtual machine and performance models for these new mechanisms
• Compilers/tools that exploit these mechanisms mostly automatically and accept user hints
• Appropriate performance balance for typical uses• Need to gain successful experience at very large scale (10-30KP) before going to ultrascale (100KP)
![Page 13: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/13.jpg)
Agenda
• Besides Architecture…• Enabling Ultra-scale Applications• Enabling New Computational Science• Sustaining Economically
![Page 14: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/14.jpg)
Scientific Process
Observe existing datafor patterns
Hypothesize modelsthat match the data
Test those modelsto understand accuracy(i.e., add new data)
**Believed first coined by Scott Studham et al., PNNL
![Page 15: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/15.jpg)
Scientific Process
Observe existing datafor patterns
Hypothesize modelsthat match the data
Test those modelsto understand accuracy(i.e., add new data)
“First Principles” computing;most of current HPC
“Dynamic Network Inference” computing**
•Query: When we know what we want and how to ask for it•Inference: When we know only somewhat what we want•Exploration: When we know little, but anticipate more
“planned serendipity”
**Believed first coined by Scott Studham et al., PNNL
![Page 16: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/16.jpg)
Example: Post-Genomic Biology
• <10% of the human genome is known to code for proteins
• Selective pressure generally removes unused genetic material
• What is the other 90% of the genome doing?– Have the raw data (genome)– Need to add other types of data (e.g., protein association info)– Multi-petabytes of data all told– Probably not a purely computational problem
![Page 17: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/17.jpg)
Differences from First Principles
• Data access patterns ~impossible to predict a priori -> low latency / global address space
• New tools for data exploration needed– need to automatically search for new, perhaps-vaguely-defined, patterns
(that foster new theory)– highly interactive/coupled with the scientist’s thought process– but beware difficulty of launching new languages
• Contents of memory much more valuable– RAS
![Page 18: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/18.jpg)
“and now for something completely different”: Star-P
• Developed by Alan Edelman and colleagues at MIT, etc.• Simple extensions to the MATLAB® language
– data parallel, MIMD, and mixed
• Builds on the existing base of MATLAB programs– broadening the market for HPC systems
• New back-end server implemented for parallel execution• Preserves key MATLAB strengths:
– very high level language– interactivity / exploration– easy visualization
“Put the fun back in supercomputing”
![Page 19: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/19.jpg)
Agenda
• Besides Architecture…• Enabling Ultra-scale Applications• Enabling New Computational Science• Sustaining Economically
![Page 20: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/20.jpg)
Key Points
• SGI retains system focus• …but uses commodity components wherever practical
– Exploit best mass-market processors (Itanium™)• augment to make suitable for wider range of HPC apps
– Use Linux fully• reap the cost benefits of reduced support of proprietary Unix™ variant
– IFB cables, EFI firmware
• Innovations for ultrascale must be relevant for wider markets– e.g., multi-paradigm computing must accelerate ISV apps
• Use new technologies to broaden the market– e.g., Star-P
![Page 21: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/21.jpg)
SGI’s systems are evolving to enable ultrascale versions of today’s
applications and enable a new type of computational science, while remaining
economically sustainable.
![Page 22: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/22.jpg)
One step ahead
![Page 23: One step ahead. The Challenges of Architectures that Grow to Petascale and can be Sustained Economically Steve Reinhardt Principal Engineer, SGI spr at.](https://reader036.fdocuments.us/reader036/viewer/2022070400/56649f155503460f94c2b133/html5/thumbnails/23.jpg)
“There are no technology-independent lessons in computer science.”
Butler Lampson, Xerox PARC