Exascale Computing Project - Driving a HUGE Change in a Changing World

2 Exascale Computing Project, www.exascaleproject.org
Leverages the planned DOE facilities acquisitions
◊ 2017 CORAL (collaboration of ORNL, ANL, LLNL)
◊ 2020 APEX (collaboration of LANL/SNL, NERSC)
◊ 2022 CORAL
◊ 2024 APEX
Exascale Computing Project - Lift the entire HPC ecosystem and
enable continued U.S. leadership in HPC
Time (CY)
Capability
2017 2021 2022 2023 2024 2025 2026 2027
10X
5X

Reaching the Elevated Trajectory will require
solving key exascale challenges
• Extreme Parallelism
– For example, an Exaflop @ 1 GHz requires a billion threads executing
• Memory and Storage
– BW, latency, and capacity are not scaling with flops
• Reliability
– Energy saving techniques and number of components drive MTBF down
• Energy Consumption
– 20MW per Exaflop has been a target since 2009
In addition, the exascale advanced architecture will need to solve
emerging data science and machine learning problems in addition
to the traditional modeling and simulations applications.

Radical, Novel, Advanced solutions are
not a Requirement but may be needed
We want the vendors to propose what they see as being needed to meet
performance, reliability, programmability, data science convergence, and
power requirements.
• If vendors can meet the requirements without needing new radical
solutions that is fine and likely preferred.
• If it involves radical new concepts, we are interested in hearing about
these solutions.
• We want to encourage vendors to propose new ideas where they
provide a path for addressing our requirements but we don’t need
novelty or “advancedness” just so we can claim things are “advanced”.

Goals of the Exascale Computing Project
Develop scientific,
engineering, and large-
data applications that
exploit the emerging,
exascale-era
computational trends
caused by the end of
Dennard scaling and
Moore’s law
Foster application
development
Create software that
makes exascale
systems usable
by a wide variety
of scientists
and engineers across
a range of applications
Ease
of use
Enable exascale by
2021 and by 2023
at least two diverse
computing platforms
with up to 50× more
computational
capability than today’s
20 PF systems, within
a similar size, cost,
and power footprint
Rich exascale
ecosystem
Help ensure continued
U.S. leadership
in architecture,
software and
applications to support
scientific discovery,
energy assurance,
stockpile stewardship,
and nonproliferation
programs and policies
US HPC
leadership

The ECP Plan
• Use a holistic/co-design approach across four focus areas:
– Application Development
– Software Technology
– Hardware Technology
– Exascale Systems
• Enable an initial exascale system to be delivered in 2021 (power
consumption and reliability requirements may be relaxed)
• Enable capable exascale systems to be delivered in 2022 as part of
the CORAL NNSA and SC facility upgrades
• System acquisitions and costs are outside of the ECP plan, and will
be carried out by DOE-SC and NNSA-ASC facilities

ECP Timeline has Two Phases – and ends 2022
R&D before facilities
select exascale systems
Targeted development for
known exascale architectures
2016 2017 2018 2019 2020 2021 2022 2023 20252024FY 2026
Exascale System #1Site Prep #1
Testbeds
Hardware Technology
Software Technology
Application Development
Facilities activities
outside ECP
NRE System #1
NRE System #2
Exascale System #2Site Prep #2

What about the 2021 System?
• The site of the 2021 system is TBD and will be decided by DOE around
June 2017.
• If the site is one of the CORAL labs, then the CORAL RFP will state:
“Within the goal of having three capable exascale systems by 2022-
2023, if an early exascale system can be delivered in 2021 and
upgraded to a capable exascale system by 2023, then provide the
upgrade as an option.”
• If the site of the 2021 system is outside the CORAL labs then (in
addition to the CORAL RFP for three 2022 systems) a separate RFP
for a single 2021 system will be released in 2018 by the chosen lab.

What is a capable exascale computing system?
ECP defines a capable exascale system as a supercomputer that
• Can solve science problems 50x faster (or more complex, for example,
more physics, higher fidelity) than the 20 PF systems of today can solve
comparable problems.
• Must use a software stack that meets the needs of a broad spectrum of
applications and workloads
• Have a power envelope of 20-30 MW
• Must be sufficiently resilient such that user intervention due to hardware
or system faults is required on the order of a week.

Diversity is Very Important to DOE
• In 2018 a single CORAL RFP will be released for delivery of three capable
exascale systems by the 2022-2023 timeframe. The RFP will also include NRE
for the systems.
• These systems will have to be designed to solve emerging data science and
machine learning problems in addition to the traditional modeling and
simulations applications.
• The DOE Leadership Computing Facility has a requirement that the ANL and
ORNL systems must have diverse architectures.
• Given the ECP goal of fostering a rich exascale ecosystem, LLNL has the
option to choose a system that is diverse from both the ANL and ORNL
systems.

There are Many Types of System Diversity
• Systems can vary from one another in many different dimensions
– System (architecture, interconnect, IO subsystem, density, resilience, etc.)
– Node (heterogeneous, homogeneous, memory and processor architectures, etc.)
– Software (HPC stack, OS, IO, file system, prog environment, admin tools, etc.)
– Hardware e.g.
• Ways Systems can be diverse
– Few big differences
– Many little differences
– Different technologies
– Different ecosystems, i.e., vendors involved
technology
scale
type
DDR NV PIM
size DIMM
Memory
on die
stacked
Fat thin accel
#cores
homo
Processor
hetero
topologies
perf
optical
Network
copper

How Diverse is Enough?
How diverse is enough? There is no hard metric, Labs will evaluate
diversity by how much it will benefit the exascale ecosystem
Having system diversity provides many advantages.
• It promotes price competition, which increases the value to DOE.
• It promotes a competition of ideas and technologies, which helps
provide more capable systems for DOE’s mission needs.
• It reduces risk that may be caused by delays or failure of a particular
technology or shifts in vendor business focus, staff or financial health.
• It helps promote a rich and healthy high performance computing
ecosystem, which is important for national competitiveness and
DOE’s strategic plan.

The ECP holistic approach
uses co-design and integration to achieve capable exascale
Application Development
Software
Technology
Hardware
Technology
Exascale
Systems
Scalable and
productive software
stack
Science and mission
applications
Hardware technology
elements
Integrated exascale
supercomputers
Correctness Visualization Data Analysis
Applications Co-Design
Programming models,
development environment,
and runtimes
Tools
Math libraries
and Frameworks
System Software,
resource management
threading, scheduling,
monitoring, and control
Memory
and Burst
buffer
Data
management
I/O and file
system
Node OS, runtimes
Resilience
Workflows
Hardware interface
Co-design centers
Proxy apps
Integration of NNSA
and Office of Science
SW efforts
PathForward
Design Space Evaluation
Testbeds
NRE

Application Scope determined by Mission Needs
• Materials discovery and design
• Climate science
• Nuclear energy
• Combustion science
• Large-data applications
• Fusion energy
• National security
• Additive manufacturing
• Many others!
• Stockpile Stewardship Annual
Assessment and Significant
Finding Investigations
• Robust uncertainty quantification
(UQ) techniques in support
of lifetime extension programs
• Understanding evolving
nuclear threats posed by
adversaries and in developing
policies to mitigate these threats
• Discover and characterize
next-generation materials
• Systematically understand
and improve chemical processes
• Analyze the extremely large
datasets resulting from the next
generation of particle physics
experiments
• Extract knowledge from systems-
biology studies of the microbiome
• Advance applied energy
technologies (e.g., whole-device
models of plasma-based fusion
systems)
Key science and technology
challenges to be addressed
with exascale
Meet national
security needs
Support DOE science
and energy missions

ECP Application Development – (1/3)
Climate
(BER)
Accurate
regional impact
assessment of
climate
change*
Combustion
(BES)
Design high-
efficiency, low-
emission
combustion
engines and
gas turbines*
Chemical
Science (BES,
BER)
Biofuel
catalysts
design; stress-
resistant crops
Fundamental
Laws (NP)
QCD-based
elucidation of
fundamental
laws of nature:
Standard
Model
validation and
beyond SM
discoveries
Materials
Science (BES)
Find, predict,
and control
materials and
properties:
Applications chosen based on National impact and DOE Offices priorities

ECP Application Development – (2/3)
Genomics
(BES)
Protein
structure and
dynamics; 3D
molecular
structure
design of
engineering
functional
properties*
Precision
Medicine for
Cancer (NIH)
Accelerate and
translate
cancer
research in
RAS pathways,
drug
responses, and
treatment
strategies*
Seismic
(EERE, NE,
NNSA)
Reliable
earthquake
hazard and risk
assessment in
relevant
frequency
ranges*
treaty verification

assembled within the limitations of shared memory hardware, in addition to making feasible the assembly
of several thousand metagenomic samples of DOE relevance available at NCBI [40].

Figure 1: NCBI Short Read Archive (SRA) and
HipMer capability growth over time, based on rough
orderofmagnitude estimates for 1% annual compute
allocation (terabases, log scale).

Figure 2. Current (green area) and projected (pink
area) scale of metagenomics data and
exascaleenabled analysis.

Furthermore, the need for efficient and scalable de novo metagenome sequencing and analysis will only
become greater as these datasets continue to grow both in volume and number, and will require exascale
level computational resources to handle the roughly doubling of metagenomic samples/experiments every
Metagenomic
(BER)
Leveraging
microbial
diversity in
metagenomic
datasets for
new products
and life forms*
Chemical
Science (BES)
Design
catalysts for
conversion of
cellulosic-
based
chemicals into
fuels,
bioproducts
Some applications also include a significant machine learning component *

ECP Applications Development – (3/3)
* Scope includes a significant data science component
Demystify
origin of
universe
and nuclear
matter
in universe*
Astrophysics
(NP)
Cosmology
(HEP)
Cosmological
probe of
standard model
(SM) of particle
physics:
Inflation, dark
matter, dark
energy*
Magnetic
Fusion
Energy (FES)
Predict and
guide stable
ITER
operational
performance
with an
integrated
whole device
model*
Nuclear
Energy (NE)
Accelerate
design and
commercialization
of next-generation
small modular
reactors*
Wind Energy
(EERE)
Increase
efficiency and
reduce cost of
turbine wind
plants sited in
complex
terrains*
Some applications also include a significant data science component *

ECP Application Development Co-Design Centers
• Center for Online Data Analysis and Reduction at the Exascale (CODAR)
• Block-Structured AMR Co-Design Center (AMReX)
• Center for Efficient Exascale Discretizations (CEED)
• Co-Design Center for Particle Applications (CoPA)
• Graph and Combinatorial Methods for Enabling Exascale Applications
(GraphEx)

ECP Software Technology Summary
• ECP will build a comprehensive and coherent software stack that will enable
application developers to productively write highly parallel applications
that can portably target diverse exascale architectures
• ECP will accomplish this by extending current technologies to exascale
where possible, performing R&D required to conceive of new approaches where
necessary, coordinating with vendor efforts, and developing and deploying
high-quality and robust software products

ECP Hardware Technology Summary
Objective: Fund R&D to design hardware that meets ECP’s Targets
for application performance, power efficiency, and resilience
• Issue PathForward and PathForward-II Hardware Architecture R&D contracts
• Participate in evaluation and review of PathForward and LeapForward
deliverables
• Lead Design Space Evaluation through Architectural Analysis, and Abstract
Machine Models of PathForward/PathForward-II designs for ECP’s holistic
co-design

Goals for PathForward (issued last year – 6 vendor awards pending)
• Improve the quality and number of competitive offeror responses to the
Capable Exascale Systems RFP
• Improve the offeror’s confidence in the value and feasibility of aggressive
advanced technology options that would be bid in response to the Capable
Exascale Systems RFP
• Improve DOE confidence in technology performance benefit,
programmability and ability to integrate into a credible system platform
acquisition

Goals of PathForward-II (planned for issue in 2017)
• Support high payoff, innovative hardware technologies and systems
technologies that may have higher risk. It is focused on component, node, and
system architecture designs that will intersect with the 2021 exascale system.
• Also of interest to the PathForward-II RFP team:
– Innovations that may enable dramatic acceleration of certain applications,
for example, delivering a 100x increase in 2021 on some classes of
applications while still being able to solve the full range of DOE applications
– Developments that promote wider diversity in the exascale ecosystem
– Innovations in power consumption, performance, programmability, reliability,
data science, machine learning, or portability
– Reducing total cost of ownership

ECP Exascale Systems Summary
• Funds Non-Recurring Engineering (NRE)
– Brings to the product stage promising hardware and software research and
integrates it into a system
– Includes application readiness R&D efforts
– Must start early enough to impact the system - more than two full years of lead time
are necessary to maximize impact
• Funds Testbeds
– ECP ECP testbeds will be deployed each year throughout the project
– FY17 testbeds will be acquired through options on existing contracts at Argonne and
ORNL
– Testbed architectures will track SC/NNSA system acquisitions and other promising
architectures

This is a very exciting time for computing in the US
• Unique opportunity to do something HUGE for the nation in HPC
• The exascale systems in 2021 and 2022 afford the opportunity for
– More rapid advancement and scaling of mission and science applications
– More rapid advancement and scaling of an exascale software stack
– Rapid investments in vendor technologies and software needed for 2021 and 2022 systems
– More rapid progress in numerical methods and algorithms for advanced architectures
– Strong leveraging of and broader engagement with US computing capability
• When ECP ends, we will have
– Prepared industry and critical applications for a more diverse and sophisticated set of
computing technologies, carrying US supercomputing well into the future
– Demonstrated integrated software stack components at exascale
– Invested in the engineering and development, and participated in acquisition and testing of
capable exascale systems

www.ExascaleProject.org
Thank you!
www.ExascaleProject.org

Exascale Computing Project - Driving a HUGE Change in a Changing World

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Exascale Computing Project - Driving a HUGE Change in a Changing World