Transcript Christine Chalk

Advanced Scientific Computing Research
FY 2015 Budget Request
presented to CASC by
Christine Chalk
Advanced Scientific Computing Research
Office of Science
U.S. Department of Energy
April 23, 2014
FY 2015 ASCR Budget
• Investment Priorities
– Exascale – Conduct research and development,
and design efforts in hardware software, and
mathematical technologies that will produce
exascale systems in 2022.
– Large Scientific Data – Prepare today’s scientific
and data-intensive computing applications to
migrate to and take full advantage of emerging
technologies from research, development and
design efforts.
– Facilities – Acquire and operate more capable
computing systems, from multi-petaflop
through exascale computing systems that
incorporate technologies emerging from
research investments.
• Specific Increases (dollars in K; includes SBIR)
– Mathematical, Computational, and
$10,428
Computer Sciences Research
– High Performance Computing and Network
Facilities
$52,479
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ASCR Budget Overview
FY 2013
Current
Approp. (prior
to SBIR/STTR)
FY 2014
Enacted
Approp.
FY 2015
President’s
Request
FY15 vs.
FY14
Advanced Scientific Computing Research
Exascale
Data
Applied Mathematics
43,341
49,500
52,155
+2,655
Exascale
Data
Computer Science
44,299
54,580
58,267
+3,687
Exascale
Data
Computational Partnerships (SciDAC)
41,971
46,918
46,918
+0
Data
Next Generation Networking for Science
11,779
15,931
19,500
+3,569
4,924
5,518
6,035
+517
146,314
172,447
182,875
+10,428
62,000
65,605
69,000
+3,395
146,000
160,000
184,637
+24,637
Research and Evaluation Prototypes
24,000
37,784
57,934
+20,150
High Performance Network Facilities and
Testbeds (ESnet)
31,610
32,608
35,000
+2,392
7,854
9,649
11,554
+1,905
271,464
305,646
358,125
+52,479
417,778
478,093
541,000
+62,907
SBIR/STTR
Total, Mathematical, Computational, and Computer
Sciences Research
High Performance Production Computing
(NERSC)
Leadership Computing Facilities
Exascale
Data
SBIR/STTR
Total, High Performance Computing and Network
Facilities
Total, Advanced Scientific Computing Research
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ASCR FY 2015 Budget Highlights* ($K)
• Exascale Crosscut
91,000†
Continue strategic investments to address the challenges of the next generation of
computing to ensure that DOE applications continue to efficiently harness the
potential of commercial hardware.
• Facilities Increase
+30,424
Begin preparations for 75-200 petaflop upgrades at each Leadership computing
facility; support move of NERSC resources into the new Computational Research and
Theory building, expansion of ESnet to support SC facilities and experiments in the US
and Europe and creation of a Computational Science Post Doctoral Training program at
the LCF’s and NERSC.
• Data Intensive Science Increase
+9,911
Continue building a portfolio of research investments that address the specific
challenges from the massive data expected from DOE mission research, including
research at current and planned DOE scientific user facilities and research to develop
novel mathematical analysis techniques to understand and extract meaning from
these massive datasets.
* Does not include increases in SBIR
† FY 2014 crosscut for Exascale was $76,364K
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Facilities
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Leadership Computing Goal
Accelerate discovery science and energy-technology innovation through use
of cutting-edge HPC systems
•
Strategies:
– Focus capability computing on high-priority, high-payoff applications
– Facilitate computing on multiple emerging architectures to exploit architectural diversity
and to mitigate risk
– Leverage commodity hardware (CPUs, memory, storage, and interconnects)
– Strive to achieve “balance” in systems among compute, memory, and storage
– Ensure applications readiness as new systems come online
– Incorporate state-of-the-art software tools, techniques, and algorithms developed by ASCR
research in applied mathematics and computer science research to ensure performance
and usability
•
Exigencies:
– Machines often are “experimental” in nature, even though based on commodity hardware
– Significant power and infrastructure needs
– Special skills needed (to achieve initial and sustain ongoing operations, to program and
use)
– Relatively small number of applications/users
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FY 2015 ASCR Facility Investments ($K)
•
NERSC (High Performance Production Computing) (+3,395):
– Operate optimally (over 90% scheduled availability)
– Move to the Computational Research and Theory Building back on the LBNL campus
– Initiate a post-doctoral training program for high-end computational science and
engineering
•
LCFs (+13,320 ALCF; +$11.3M OLCF)
– Operate optimally (over 90% scheduled availability)
– Prepare for planned 75-200 petaflop upgrades in the 2017-2018 timeframe
• Purchase and install long –lead time items such as cooling towers, chillers,
transformers, heat exchangers, pumps, etc.
– Initiate a post-doctoral training program for high-end computational science and
engineering
•
High Performance Network Facilities and Testbeds (+$2.3M)
– Operate optimally (99.99% reliability)
– Coordinate with other agencies to ensure the availability of next generation of optical
networking from domestic sources
– Expansion of 100 Gbs network to support interim traffic growth
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Leadership Computing Facilities (+$24,637 in $K)
•
Leadership Computing Facilities (LCF) Mission: Provide the computational and data
science resources required to solve the most challenging of scientific & engineering
problems
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•
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2 architectures to address diverse and growing computational needs of the scientific
community.
Projects receive computational resources typically 100x greater than generally available.
Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) completed
upgrades in FY 2013. Currently the ALCF has a 10 PF IBM Blue Gene and the OLCF has a 27
PF Cray XK7.
Even with the increased resources, requests for allocations from both the Innovative and
Novel Computational Impact on Theory and Experiment (INCITE) and ASCR Leadership
Computing Challenge (ALCC) on the LCF remain oversubscribed by a factor of 3 and
expected to grow.
Planning, site preparation and delivery of next upgrades takes 4-5 years. The LCFs are
working with LLNL on a joint procurement for resources in the 2017-2018 timeframe. The
process for the next LCF upgrades has started
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•
•
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Mission need statement (CD-0) signed January, 2013 for the delivery of 150-400 petaflops (PF)
(75-200 PF at each LCF to provide architectural diversity). Upgrades in this range would increase
the capability of the LCFs by a factor of 4-10.
The Acquisition Strategy ( CD-1/CD-3a) was approved in October, 2013 allowing the labs to
finalize a Request for Proposals for the upgrades.
RFP released in January 2014 ; proposals received February 2014 and under review.
Baseline approval and final contract negotiations with selected vendors are anticipated in
Q1FY15
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Mission Need for LCF 2017-2018 Upgrades
Science challenges that can be tackled with proposed upgrades:
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Energy Storage: Develop multiscale, atoms-to-devices, science-based predictive simulations of cell performance characteristics,
safety, cost, and lifetime for various energy storage solutions along with design optimizations at all hierarchies of battery (battery
materials, cell, pack, etc.).
Nuclear Energy: Develop of integrated performance and safety codes with improved uncertainty quantification and bridging of
time and length scales. Implement next-generation multiphysics, multiscale models. Perform accurate full reactor core calculations
with 40,000 fuel pins and 100 axial regions.
Combustion: Develop of fuel efficient engines through3D simulations of high-pressure, low-temperature, turbulent lifted diesel jet
flames with biodiesel or rate controlled compression ignition with fuel blending of alternative C1-C2 fuels and n-heptane. Continue
to explore the limits of high-pressure, turbulent combustion with increasing Reynolds number.
Fusion: Perform integrated first-principles simulation including all the important multiscale physical processes to study fusionreacting plasmas in realistic magnetic confinement geometries.
Electric Grid: Optimization the stabilizing the energy grid while introducing renewable energy sources; incorporate more realistic
decisions based on available energy sources.
Accelerator Design: Simulate ultra-high gradient laser wakefield and plasma wakefield accelerator structures.
Catalysis Design: Enable end-to-end, system-level descriptions of multifunctional catalysis including uncertainty quantification and
data-integration approaches to enable inverse problems for catalytic materials design.
Biomass to Biofuels: Simulate the interface and interaction between 100-million-atom microbial systems and cellulosic biomass,
understanding the dynamics of enzymatic reactions on biomass. Design of superior enzymes for conversion of biomass.
High resolution climate modeling: Simulate high resolution events by incorporating scale aware physics that extends from
hydrostatic to nonhydrostatic dynamics. Incorporate cloud resolving simulation codes that couple with a dynamically responding
surface.
Rapid climate and earth system change: Adequately simulate physical and biogeochemical processes that drive nonlinear
responses in the climate system, e.g., rapid increases of carbon transformations and cycling in thawing permafrost; ice sheet
grounding line dynamics with ocean coupling that lead to rapid sea level rise; dynamics of teleconnections and system feedbacks
within e.g. the (meridional) ocean circulation that alter global temperature and precipitation patterns.
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Anticipated LCF System Upgrades
System attributes
2013
“2017”
ALCF/MIRA
OLCF/TITAN
10 PF
27 PF
75-200 Petaflop/sec
4.8MW (Max)
2.8MW (Typical)
8.2 MW (Max)
5.5 MW(Typical)
15-20 MW (Max)
12-16 MW (Typical)
0.8 PB
0.7 PB
4 PB
Node performance
204.8GF
1,452 GF
2-10 TF
Node memory BW
42.6GB/s
Opteron -51.2 GB/s
Kepler - 180 GB/s
Up to 1 TB/s to fast
memory
UP to 500 GB/s to bulk
memory
Node concurrency
16 cores, each
with 4 hardware
threads
Operton – 16
Kepler – 2,688 CUDA Cores
> 60 cores
System size (nodes)
49,152 nodes
18,700 nodes
8,000-50,000 nodes
20GB/s
6.4GB/s
> 25 GB/sec
System peak
Power
System memory
Total Node Interconnect BW
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ALCF Upgrade Requirements
Space: Theory and Computing Sciences Building Expansion
• 15,000 SF for computer and 15,000 SF for mechanical, electrical and plumbing
• Adjacent to laboratory-planned Electrical Substation and Chilled Water Plant
expansion
• Raised floor load will be 750 PSF
Power:
• 15-30MW peak of power and equivalent
• Computer 18.5 MW
• Data Storage 1.0 MW
• Computational Infrastructure 0.5 MW
Cooling:
• Cooling water supply at 80° F
• Two cooling towers provide cooling when ambient temperature is ≤ 73°
• Chillers supplements cooling when ambient temperature is >73° F
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OLCF Upgrade Requirements
Space: Computational Sciences Building Expansion 1st floor
• 10,000 SF of unfinished shell space
• Adjacent to planned Central Energy Plant expansion
• Slab on grade – no floor loading issues
Power:
• 20MW peak technical power
• Computer 18.5 MW
• Data storage 1.0 MW
• Computational infrastructure 0.5 MW
Cooling:
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20MW (5700 tons) total cooling required
Chilled water temps 55-65° F
Humidity control in computer center
N+1 chillers for reliability /maintainability
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Post-Doc Training Program
• The Nation needs highly trained workforce of computational scientists to
run perform simulations across fields ranging from national security to basic
energy science to engineering
• ASCR facilities report that it takes up to 18 months to locate and recruit
qualified computational scientists.
• Numerous Advanced Scientific Computing Advisory Committee (ASCAC)
reports have recommended investing more to build workforce capabilities
• To address these needs ASCR proposes a Computational Scientists for
Energy, Environment and National Security (CSEEN) Training program
– Sited at ASCR facilities to attract a diverse set of candidates
– Because of increasing processor count and architectural diversity in future computing
resources, many application codes and algorithms will need to be re-written. CSEEN post
docs will have access to the leading edge computers as well as experienced staff at the
ASCR facilities to broaden their computational skillset.
– Each facility is associated with a University with a strong computational science program.
If there is a perceived gap in CSEEN Post Docs’ background there is support for additional
course work.
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R&E Prototypes
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FastForward: In FY12, Research and Evaluation Prototypes activity worked with LLNL to
award $95M (total, including cost sharing, over two years) for innovative R&D on critical
technologies – memory, processors and storage – needed to deliver next generation
capabilities within a reasonable energy footprint.
– Funded Projects:
• AMD: processors and memory for extreme systems;
• IBM : memory for extreme systems;
• Intel Federal: energy efficient processors and memory architectures;
• Nvidia: processor architecture for exascale computing at low power; and
• Whamcloud: storage and I/O (input/output) – bought by Intel.
FY 2015 increases support taking FastForward research to the next level
– Lab/vendor partnerships (+12,216)
• develop prototypes of the most promising mid-term technologies from the Fast
Forward program for further testing
– Nonrecurring engineering (+7,934)
• Incorporate near-term technologies from Fast Forward into planned facility upgrades
at NERSC, ALCF and OLCF.
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Non Recurring Engineering (NRE) Costs
• Component of Research and Evaluation Prototypes
• Previous R&E investments beginning in 2007-2008
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Support of IBM-ANL-LLNL R&D contract
for design and development of the IBM
Blue Gene P/Q systems
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Support of Cray component of DARPA
HPCS program
Outcome
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Support to develop and scale compilers,
storage systems and debuggers to
support use of graphical processing units
Outcome
Outcome
• Because of vendor development schedules, the earliest that results from
today’s Fast Forward investments can be in ASCR systems is 2020. Thus, NRE
funds will be used to
– Scale up proposed systems on vendor’s roadmap for deployment in the LCFs in 2017-2018
– Harden near-term vendor’s research for use in proposed systems to move the architectures closer to
pre-exascale.
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LCF Staff
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Over the past 10 years, each LCF has created an staff experienced in deploying and
operating “serial 1” supercomputers to deliver scientific discovery. Because of their
extremely specialized skill sets many LCF staff members occupy leadership roles in
international standards activities, users groups, and developments groups; are
regularly engaged by national and international advisory panels on highperformance scientific computing; and asked to play leadership roles in scientific and
technical meetings to more broadly share knowledge on progress in HPC.
They have created a new model for providing user support where each project is
assigned their own specialist to ensure scientific discovery through the effective use
of LCF systems and emerging systems by
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assessing and improving the algorithms used by the applications;
helping optimize code for the users’ applications,
streamlining the work flow, and
solving any computer issues that arise.
A recent Independent review of the LCF’s upgrade plans found LCF organizations have a
demonstrated track record of multiple, successful deployments of new machines,
machine upgrades, and development of necessary infrastructure and ancillary facilities
to house and maintain leadership computing operations.
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Innovative and Novel Computational Impact on Theory and Experiment
INCITE is an annual, peer-review allocation program that provides
unprecedented computational and data science resources
• 5.8 billion core-hours awarded for 2014 on the
27-petaflops Cray XK7 “Titan” and the
10-petaflops IBM BG/Q “Mira”
• Average award: 78 million core-hours on Titan
and 88 million core-hours on Mira in 2014
• INCITE is open to any science domain
• INCITE seeks computationally intensive,
large-scale research campaigns
Call for Proposals
The INCITE program seeks
proposals for high-impact
science and technology
research challenges that require
the power of the leadershipclass systems. Allocations will
be for calendar year 2015.
April 16 – June 27, 2014
Contact information
Julia C. White, INCITE Manager
[email protected]
Leadership-class resources at INCITE
INCITE
Eligibility Info
INCITE is for researchers who have capability, time-tosolution, or computer architecture and data infrastructure
requirements that can’t be met by any other resource.
INCITE is open to researchers worldwide; US collaboration
is encouraged but not required. DOE funding is not
required.
INCITE
Access Details
• Early access to prepare for INCITE:
See the ALCF and OLCF Director’s
Discretionary programs.
– ALCF: www.alcf.anl.gov
– OLCF: www.olcf.ornl.gov
• INCITE information
– www.doeleadershipcomputing.org
Exascale and Data Intensive Science
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Exascale Computing
• In partnership with NNSA
• “All-in” approach:
– Mission-critical applications for
National security & extreme scale science
– System software/stacks
– Acquisition of computer systems
• Exaflops sustained performance
– Approximate peak power 20-30 MW
• Productive system
– Usable by a wide variety of scientists
– “Easier” to develop software & to
manage the system
• Based on marketable
technology
– Not a “one off” system
– Scalable, sustainable technology
• Major step in architectural complexity – not business as usual
• Deployment in ~2023
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Path Toward Exascale -- $91 million in FY 2015 ($K)
FY 2013
Current
Approp.
FY 2014
Enacted
Approp.
FY 2015
President’s
Request
FY2015 Exascale Investments
Mathematics, Computational and
Computer Science Research
Applied Mathematics
49,500
52,155
5,000
5,000
5,000
Computer Science
44,299
54,580
58,267
Exascale: Extreme scale, Advanced
Architectures
12,580
17,580
20,000
Computational Partnerships (SciDAC)
41,971
46,918
46,918
Exascale: Co-Design
12,705
16,000
16,000
Continues support for Co-Design activities, including data intensive
science partnerships started in FY 2014
Research and Evaluation Partnerships
24,000
37,784
57,934
Note: $7.9M in FY 15 is for non recurring engineering costs for
facility upgrades.
Exascale : Platform R&D and Critical
Technologies
24,000
37,784
50,000
Initiates conceptual design studies for prototypical exascale
systems from application workflow to hardware structure and
system software; continues support for Fast Forward investments
in critical technologies and Design Forward investments in systemlevel engineering efforts with high performance computer vendors.
Exascale Total
54,285
76,364
91,000
Exascale: Uncertainity Quantification
Continues support for awards made in 2013 on “UQ Methods for
Extreme-Scale Science.” These efforts will improve the fidelity and
predictability of DOE Simulations
Supports new research addressing in situ methods, workflows, and
proxy applications for data management, processing, analysis and
visualization; continues support for research into advanced
architectures, software environments and operating systems.
High Performance Computing and
Network Facilities
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Office of Science and “Big Data”
• SC has not been viewed historically by many not to be a
player in “big data”
• However, examples within SC abound:
– Data from large-scale experiments (HEP, BES); medium-scale experiments
(BER)
– Observational data (BER/Climate, BER/Environment, HEP)
– Simulation results (BER/Climate, BES, HEP, NP, FES)
• SC has significant infrastructure devoted to data
– ASCR: NERSC and the Leadership Computing Facilities
– HEP: data architecture devoted to LHC
• Big data and big computing go hand-in-hand – cannot have
one without the other
• Workflows are emerging at large experimental facilities that
join with high-end computing
– ALS, APS, LCLS, SNS
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Mission: Extreme Scale Science
Data Explosion
Genomics
Data Volume increases
to 10 PB in FY21
High Energy Physics
(Large Hadron
Collider)
15 PB of data/year
Light Sources
Approximately
300 TB/day
Climate
Data expected to be
hundreds of 100 EB
Driven by exponential technology
advances
Data sources
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Scientific Instruments
Scientific Computing Facilities
Simulation Results
Observational data
Big Data and Big Compute
• Analyzing Big Data requires processing (e.g.,
search, transform, analyze, …)
• Extreme scale computing will enable timely
and more complex processing of increasingly
large Big Data sets
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ASCR Research Investments in “Big Data”
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Applied Math (+$2,655):
– Development of mathematical algorithms that accommodate the spatial and temporal variation in
data and account for the characteristics of sensors as needed and adaptively reduce data
– Development of new compression techniques
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Computer Science (+3,687)
– Develop new paradigm for generating and executing dynamic workflows that include the
development of new workflow engines and languages that are semantically rich and allow
interoperability or interchangeably in many environments
– Development of scalable and interactive visualization methods for ensembles, multivariate and
multiscale data
– Define components and associated Application Programing Interfaces for storing , annotating and
accessing scientific data; support development of standards
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Next Generation Networking for Science (+$3,569)
– Develop new methods for scheduling data movement over the WAN that includes understanding
replication policies, data architectures and subset access mechanisms
– Create new methods for rapid and scalable collaborative analysis and interpretation
– Construct a cyber framework that supports complex real-time analysis and knowledge navigation,
integration and creation processes.
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SC/NNSA Partnership
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ASCR-NNSA Partnership
 DOE Exascale Program is a partnership
between Office of Science and NNSA
 Joint:
• Management via 2011 MOU between the
DOE Office of Science and NNSA
• Program planning and execution of technical
R&D
• Fast Forward, Design Forward
• Development of Exascale Roadmap
• Procurements of major systems
• Lab executive engagement via “E7”
• ANL, LANL, LBNL, LLNL, ORNL, PNNL, SNL
• Periodic PI meetings and workshops
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Joint Procurements with NNSA
• In January, 2013, DOE Office of Science approved the mission need
for LCF upgrades to be installed in 2017-2018
• Because of the timing of acquisitions ANL and ORNL along with
Lawrence Livermore National Laboratory will collaborate on a joint
procurement for upgrades.
• Will result in two diverse platforms for the LCFs
• Collaboration is a win-win for all parties:
– Reduces the number of RFPs vendors have to respond to
– Allows pooling of R&D funds
– Supports sharing technical expertise between Labs
– Should improve the number and quality of proposals
– Strengthens the alliance between SC/NNSA on road to exascale
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