sc11 jen-hsun huang keynote
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NVIDIA Confidential
Exascale An Innovator’s Dilemma
Jen-Hsun Huang, CEO SC11, Seattle, Washington | Nov. 15, 2011
"Generally, disruptive innovations were
technologically straightforward,
consisting of off-the-shelf components
put together in a product architecture
that was often simpler than prior
approaches. They offered less of what
customers in established markets
wanted and so could rarely be initially
employed there. They offered a
different package of attributes valued
only in emerging markets remote from,
and unimportant to, the mainstream.”
NVIDIA Confidential
A History of Amazing Advances
1988 1998 2009
TERAFLOPS
PETAFLOPS
ZETTAFLOPS
GIGAFLOPS
EXAFLOPS
Cray T3E-1200 0.9 TF
Cray XT-5 “Jaguar” 1.8 PF, 7 MW
Cray Y-MP8 2.7 GF, 0.15 MW
Advances with Dennard Scaling
1988 1998 2009
TERAFLOPS
PETAFLOPS
ZETTAFLOPS
GIGAFLOPS
EXAFLOPS
Cray T3E-1200 0.9 TF
Cray XT-5 “Jaguar” 1.8 PF, 7 MW
Cray Y-MP8 2.7 GF, 0.15 MW
½ L every 4 yrs 8X – same P
1.68X per/W CAGR
End of Dennard Scaling
1988 1998 2009
TERAFLOPS
PETAFLOPS
ZETTAFLOPS
GIGAFLOPS
EXAFLOPS
Cray T3E-1200 0.9 TF
Cray XT-5 “Jaguar” 1.8 PF, 7 MW
Cray Y-MP8 2.7 GF, 0.15 MW
½ L every 4 yrs 8X @ 4X P
1.19X per/W CAGR
Supercomputing is Power Limited
1988 1998 2009
TERAFLOPS
PETAFLOPS
ZETTAFLOPS
GIGAFLOPS
2012 2035
EXAFLOPS
Cray T3E-1200 0.9 TF
Cray XT-5 “Jaguar” 1.8 PF, 7 MW
Cray Y-MP8 2.7 GF, 0.15 MW
70 PF, 20 MW
100 PF, 20 MW
1 EF, 20 MW
CPU-only “Titan” 6 PF, 8.6 MW
2022 2019
CPUs Fast But Complex
Optimized for single-threaded performance
~50X energy to schedule instruction than the operation
~20X energy to move data across chip than the calculation
Super Efficient Processors Needed
Many simple processors with minimal overhead
Locality reduces data movement energy
Poor single-threaded performance
Innovator’s Dilemma!
PRINCIPLE #1 Companies depend on customers
and investors for resources.
Clayton M. Christensen (1997) The Innovator’s Dilemma:
When New Technologies Cause Great Firms to Fail
PRINCIPLE #2 Small markets don’t solve growth
needs of large companies.
Clayton M. Christensen (1997) The Innovator’s Dilemma:
When New Technologies Cause Great Firms to Fail
GPU Computing “New Market” Disruption
Disruptive technologies underperform established products in mainstream markets.
Cheaper, smaller, and frequently more convenient.
Clayton M. Christensen (1997) The Innovator’s Dilemma:
When New Technologies Cause Great Firms to Fail
Nagasaki University Professor Tsuyoshi Hamada’s Homemade supercomputer
GPU Computing
GPUs with CUDA >350,000,000
Toolkit Downloads >1,000,000
Active Developers >120,000
Universities Teaching GPU Computing >475
HPC OEMs offer GPU Clusters 100%
World’s First
Whole H1N1 Virus Simulation
Lifecycles of fish in Australia
University of Melbourne
Stars and galaxies 12.5B years ago
University of Groningen
Neural networks in a self-learning robot
The University of Plymouth
Directives
65x in 2 Days 5.6x in 5 Days 4.7x in 4 Hours
2012 2022
PETAFLOPS
2019 2035
The Road to Exascale
70 PF, 20 MW
100 PF, 20 MW
1 EF, 20 MW
CPU-only “Titan” 6 PF, 8.6 MW
GPU-Accelerated “Titan”
20 PF, 8.6 MW
1 EF, 20 MW
ZETTAFLOPS
2012
ZETTAFLOPS
PETAFLOPS
2035
The Road to Exascale
70 PF, 20 MW
100 PF, 20 MW
1 EF, 20 MW
CPU-only “Titan” 6 PF, 8.6 MW
GPU-Accelerated “Titan”
20 PF, 8.6 MW
1 EF, 20 MW
1 EF, 20 MW
2022 2019
2012
ZETTAFLOPS
PETAFLOPS
2035
The Road to Exascale
70 PF, 20 MW
100 PF, 20 MW
1 EF, 20 MW GPU-Accelerated “Titan”
20 PF, 8.6 MW
1 EF, 20 MW
100 EF, 20 MW
2022 2019
CPU-only “Titan” 6 PF, 8.6 MW
Huge Markets Support GPU
Mobile
1,000M
PCs
400M
Console
20M
Workstation
5M
5 Watts “Teraflops”
1997 2019
ASCI Red @ Sandia Labs
DEMO: BATTLEFIELD 3
100 Watts “Tens” of Teraflops
2004 2019
Red Storm @ Sandia Labs
DEMO: ASSASSIN’S CREED
1000 Watts
2006 2019
“Hundreds” of Teraflops
Blue Gene @ LLNL
DEMO: MAYA
DEMO: FUMEFX
One Disruption Enables Another
‘Super’ Computing From Super Computers to Super Phones
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