SlideShare a Scribd company logo
European
Processor Initiative
& RISC-V
Prof. Mateo Valero
BSC Director
9/May/2018 RISC-V Workshop, Barcelona
Barcelona Supercomputing Center
Centro Nacional de Supercomputación
Spanish Government 60%
Catalan Government 30%
Univ. Politècnica de Catalunya (UPC) 10%
BSC-CNS is
a consortium
that includes
BSC-CNS objectives
Supercomputing services
to Spanish and
EU researchers
R&D in Computer,
Life, Earth and
Engineering Sciences
PhD programme,
technology transfer,
public engagement
People and Resources Data as of 31st of December 2017
Context: The international Exascale challenge
• Sustained real life application performances, not just
Linpack…
• Exascale will not just allow present solutions to run faster,
but will enable new solutions not affordable with today HPC
technology
• From simulation to high predictability for precise medicine,
energy, climate change, autonomous driven vehicles…
• The International context (US, China, Japan and EU…)
• The European HPC programme
• The European Processor initiative
• BSC role
Top5 November 2017 list (compact view)
Rank Site Computer Procs Rmax Rpeak Mflops/Watt
1 Wuxi, China Sunway SW26010 260C 10.649.600 93.015 125.436 6.051
2 Guangzhou, China Xeon E5-2692+Phi
3.120.000
33.863 54.902 1.902
2736000
3 CSCS, Switzerland Cray XC50, Xeon E2690 12C+P100
361.760
19.590 25.326 8.622
297920
4 JAMEST, Japan ZettaScaler Xeon D-1571, PEZY-SC2
19860000
19.135 28.192 14.173
19840000
5 DOE/SC/Oak Ridge, US Cray XK7, Opteron 16C+K20
560.640
17.590 27.113 2.143
261632
6 DOE/NNSA/LLNL, US BlueGene/Q, BQC 16C 1.572.864 17.173 20.133 2.177
7 DOE/NNSA/LANL/SNL, US Cray XC40, IXeon Phi 7250 (KNL) 979.968 14.137 43.902 3.678
8 DOE/SC/LBNL/NERSC, US Cray XC40, Xeon Phi 7250 (KNL) 622.336 14.015 27.881 3.558
9 JCA, Japan PRIMERGY, Xeon Phi 7250 (KNL) 556.104 13.555 24.913 4.896
10 Riken/AICS, Japan K computer, SPARC64 705.024 10.510 11.280 830
11 DOE/SC/Argonne, US BlueGene/Q, Power BQC 16C 786.432 8.587 10.066 2.177
12 TACC Texas, US PowerEdge, Xeon Phi 7250 (KNL), 368.928 8.318 18.216 N/A
13 GSIC-TIT, Japan SGI, Xeon E5,Tesla P100
135.828
8.125 12.127 10.258
120736
14 CINECA, Italy Lenovo, Xeon Phi 7250 68C, KNL 314.384 7.471 15.372 N/A
15 UKMET, UK Cray XC40, Xeon E2695 18C 241.920 7.039 8.129 N/A
16 BSC, Spain Lenovo, Xeon Platinum 8160 24C 153.216 6.471 10.296 3.965
According to HPL According to HPCG benchmark
Top5
Rank Name Country Rmax Rpeak
%
Efficiency
1
Sunway
TaihuLight
China 93,015 125,436 74.15 %
2 Tianhe-2
China
33,863 54,902
61.68%
3 Piz Daint
Switzerland
19,590 25,326
77.35%
4 Gyoukou
Japan
19,135 28,192
67.87%
5 Titan
US
17,590 27,113
64.87%
6 Sequoia US 17,173 20,133 85.30%
7 Trinity US 14,137 43,902 32.20%
8 Cori US 14,015 27,881 50.27%
9
Oakforest-
PACS
Japan 13,555 24,913 54.41%
10 K Computer Japan 10,510 11,280 93.17%
Rank Name Rmax Rpeak
%
Efficiency
1 K Computer 603 11,280 5.34%
2 Tianhe-2 580 54,902 1.06%
3 Trinity 546
43,902
1.24%
4 Piz Daint 486
25,326
1.92%
5
Sunway
TaihuLight
481
125,436
0.38%
6
Oakforest-
PACS
385
24,913
1.54%
7 Cori 355
27,881
1.27%
8 Sequoia 330
20,133
1.64%
9 Titan 322
27,113
1.19%
10 Mira 167 10,066 1.66%
According to HPL According to HPCG benchmark
Top5
Rank Name Country Rmax Rpeak
%
Efficiency
1
Sunway
TaihuLight
China 93,015 125,436 74.15 %
2 Tianhe-2
China
33,863 54,902
61.68%
3 Piz Daint
Switzerland
19,590 25,326
77.35%
4 Gyoukou
Japan
19,135 28,192
67.87%
5 Titan
US
17,590 27,113
64.87%
6 Sequoia US 17,173 20,133 85.30%
7 Trinity US 14,137 43,902 32.20%
8 Cori US 14,015 27,881 50.27%
9
Oakforest-
PACS
Japan 13,555 24,913 54.41%
10 K Computer Japan 10,510 11,280 93.17%
16
Mare
nostrum
Spain
6,471
10,296 62,85%
Rank Name Rmax Rpeak
%
Efficiency
1 K Computer 603 11,280 5.34%
2 Tianhe-2 580 54,902 1.06%
3 Trinity 546
43,902
1.24%
4 Piz Daint 486
25,326
1.92%
5
Sunway
TaihuLight
481
125,436
0.38%
6
Oakforest-
PACS
385
24,913
1.54%
7 Cori 355
27,881
1.27%
8 Sequoia 330
20,133
1.64%
9 Titan 322
27,113
1.19%
10 Mira 167 10,066 1.66%
15
Mare
Nostrum
122 10,296 1,18%
Rank Previous rank Machine Country Number of cores GTEPS
1 1 K computer Japan 663,552 38,621
2 2 Sunway TaihuLight China 10,599,680 23,755
3 3 DOE/NNSA/LLNL Sequoia USA 1,572,864 23,751
4 4
DOE/SC/Argonne National
Laboratory Mira
USA 786,432 14,982
5 5 JUQUEEN Germany 262,144 5,848
6 new ALCF Mira - 8192 partition United States 131,072 4,212
7 6 ALCF Mira - 8192 partition USA 131,072 3,556
8 7 Fermi Italy 131,072 2,567
9 new ALCF Mira - 4096 partition United States 65,536 2,348
10 8 Tianhe-2 (MilkyWay-2) China 196,608 2,061
8
Graph500
Rank
TOP500
Rank
System Cores
Rmax
(TFlop/s)
Power
(kW)
Power Efficiency
(GFlops/watts)
1 259
Shoubu system B - PEZY Computing
RIKEN -Japan
794,400 842.0 50 16.84
2 307
Suiren2 - PEZY Computing
KEK -Japan
762,624 788.2 47 16.77
3 276
Sakura - PEZY Computing
PEZY Computing K.K. -Japan
794,400 824.7 50 16.49
4 149
DGX SaturnV Volta - NVIDIA Tesla V100
NVIDIA Corporation -United States
22,440 1,070.0 97 11.03
5 4
Gyoukou - PEZY-SC2 700Mhz
Japan
19,860,000 19,135.8 1,350 14.17
6 13
TSUBAME3.0 - NVIDIA Tesla P100 SXM2
Japan
135,828 8,125.0 792 10.26
7 195
AIST AI Cloud - NVIDIA Tesla P100 SXM2
Japan
23,400 961.0 76 12.64
8 419
RAIDEN GPU subsystem - NVIDIA Tesla
P100
Japan
11,712 635.1 60 10.59
9 115
Wilkes-2 - NVIDIA Tesla P100
University of Cambridge - United Kingdom
21,240 1,193.0 114 10.46
10 3
Piz Daint - NVIDIA Tesla P100
Switzerland
361,760 19,590.0 2,272 8.62
33 16
MareNostrum- Lenovo SD530
Barcelona Supercomputing Center
Spain
153,216 6,470.8 1,632 3.97
9
Green500
Application processor performance
MN3-MN4
Application Cores Performance
WRF
256 1.37
128 1.06
GROMACS
1024
192 1.19
NAMD
2048 1.31
1024 1.17
728 1.25
512 1.20
VASP
64 2.2
32 2.0
HPL
96 2.24
48 2.21
From MN3 to MN4
MareNostrum4
Total peak performance: 13,7 Pflops
General Purpose Cluster: 11.15 Pflops (1.07.2017)
CTE1-P9+Volta: 1.57 Pflops (1.03.2018)
CTE2-Arm V8: 0.5 Pflops (????)
CTE3-KNH?: 0.5 Pflops (????)
MareNostrum 1
2004 – 42,3 Tflops
1st Europe / 4th World
New technologies
MareNostrum 2
2006 – 94,2 Tflops
1st Europe / 5th World
New technologies
MareNostrum 3
2012 – 1,1 Pflops
12th Europe / 36th World
MareNostrum 4
2017 – 11,1 Pflops
2nd Europe / 13th World
New technologies
Worldwide HPC roadmaps
From Tianhe-2..
…to Tianhe-2A
with domestic
technology.
From K computer…
… to Post K
with domestic
technology.
From the PPP for
HPC…
to future PRACE
systems…
…with domestic
technology
with domestic
technology.
IPCEI on HPC
?
US launched RFP for Exascale (April 2018)
• To develop at least two new exascale supercomputers for the DOE at
a cost of up to $1.8 billion
• The deployment timeline for these new systems begins in the third
quarter of 2021, with ORNL’s exascale supercomputer, followed by a
third quarter 2022 system installation at LLNL. The ANL addition or
upgrade, if it happens, will also take place in the third quarter of
2022.
• The new systems can’t exceed 40 MW, with the preferred power
draw in the 20 to 30 MW (including exascale, counting storage,
cooling and any other auxiliary equipment )
• The other critical requirement is that the ORNL and ANL systems are
architecturally diverse from one other
• Proposals are due in May, the bidders will be selected before the end
of the Q2
• Each system is expected to cost between $400 to $600 million
second quarter.
Worldwide HPC roadmaps
From Tianhe-2..
…to Tianhe-2A
with domestic
technology.
From K computer…
… to Post K
with domestic
technology.
From the PPP for
HPC…
to future PRACE
systems…
…with domestic
technology
with domestic
technology.
IPCEI on HPC
?
EU HPC Ecosystem
• Specifications of exascale prototypes
• Technological options for future systems
• Identify applications for co-
design of exascale systems
• Innovative methods and
algorithms for extreme
parallelism of traditional &
emerging applications
• Collaboration of HPC
Supercomputing
Centres and application CoEs
• Provision of HPC capabilities
and expertise
Centers of Excellence in HPC applications
HPC
Ecosystem
EXDCI
Eurolab-4-HPC
ExCAPE
GreenFLASH
READEX
ESCAPE
INTERTWINE
ALLScale
ANTAREX
ExaFLOW
ComPat
NLAFET
ExaHYPE
NEXTGenIO
SAGE
ExaNEST
ExaNoDe
ECOSCALE
EXTRA
Mont-Blanc 3
Mango
HPC R&D: H2020 current landscape
BioExcel COEGSS EoCoE E-CAM ESiWACE MAX NOMAD PoP
Centres of Excellence
Biomolecular
Global
systems
Energy Simulation
Modelling
Weather
Climate
Materials Performance
optimisation
Computational
Biomedicine
CompBioMed
FET & e-Infra Calls WP2014-2015
18
A big challenge, and a huge opportunity for Europe
18
Extend current mobile chips with the needed HPC features
– Explore the use vector architectures in mobile accelerators (vector processor ARM-based, 15+ Teraflops chip, 150
watts)… unique opportunity for Europe
– One design for all market segments: mobile, data centers, supercomputers
2011 2012 2013 2014 2015 2016 2017
256 nodes
250 GFLOPS
1.7 Kwatt
120 TFLOPS
80 Kwatt
200 PFLOPS
~10 MWatt
Built with the best
of the market
Built with the best
that is coming
What is the best
that we could do?
GFLOPS/W
Integrated
ARM + GPU
Mont-Blanc HPC Stack for ARM
Industrial applications
System software
Hardware
Applications
World Top 20 machines (status November 2017)
Europe has only 4 machines in world top 20
■ Italy (CINECA) – Nr 14
■ UK (Meteorological office) – Nr 15
■ Spain (BSC, Barcelona) – Nr 16
■ Germany (HLRS, Stuttgart) – Nr 19
EU not in HPC world leaders
BSC and the European Commission
Final plenary panel at ICT -
Innovate, Connect, Transform
conference, 22 October 2015
Lisbon, Portugal.
The transformational impact of excellent science in
research and innovation
Paris, 27 October 2015
European Commission President
Jean-Claude Juncker
"Our ambition is for Europe to become one of
the top 3 world leaders in high-performance
computing by 2020"
The European Commission and HPC
Vice-President Andrus Ansip
"I encourage even more EU countries to
engage in this ambitious endeavour"
• Ministers from seven MS (France, Germany, Italy,
Luxembourg, Netherlands, Portugal and Spain) sign a
declaration to support the next generation of
computing and data infrastructures
Digital Day Rome, 23 March 2017
The EuroHPC Declaration
Declaration signed in Rome, March 23rd, 2017 by:
Agree to work towards the
establishment of a
cooperation framework -
EuroHPC - for acquiring and
deploying an integrated
exascale supercomputing
infrastructure that will be
available across the EU for
scientific communities as well
as public and private partners
France Germany Italy Luxembourg Netherlands Portugal Spain
Belgium Slovenia Bulgaria Switzerland Greece Croatia
Six more countries signed the Declaration:
EuroHPC latest news:
Europa portail: (January 2018)
http://europa.eu/rapid/press-release_IP-18-64_en.htm
FET 2014-2017
HW/SW building blocks and co-design
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
l l l l l l l l ll
pre-exascale
HPC Ecosystem development
FET 2020: extreme scale HPC
systems and applications
exascale
FET 2019: extreme scale computing
& data for key applications
LEIT-ICT 2017-2020: Framework Programme Agreement (FPA)
Low-power/Microprocessor HPC
LEIT-ICT 2018: Extreme Scale
Demonstrators
Technology &
Applications
development
integration
in co-design
procurement
Widening access
and services
LEIT-ICT 2018: HPC / Big Data enabled
Large-scale Test-beds and Applications
HPC timeline in H2020 LEIT/FET
(indicative)
EPI 23 partners, from research to industry
from consortium to EU high
tech fabless
EU - FPA Semiconductor
EPI
Common
Platform
Fabless company
Industrial hand of EPI
Incorporated by a
couple EPI members
and external investors
1st EPI production
Three streams
General purpose and Common Platform
• ARM SVE or other candidates…
• BULL: System integrator  chip integrator
Accelerator
• RISC-V
• EU design: BSC, CEA, Chalmers, ETHZ, EXTOLL, E4,
FORTH, Fraunhofer, IST, UNIBO, UNIZG, Semidynamics
Automotive
• Infineon, BMW…
2018 2019 2020 2021 2022 2023 2024 2025
CPU?
ACCEL.
HPC System
PreExascale
HPC
Chip &
system
Accel.
Chip &
system
Core
Technolog
y
KeyMarkets
HPC
Chip &
system
Accel.
Chip &
system
Gen 1 Gen 2
HPCCARS
Automotive CPU
Proof of Concept
Gen 3
Automotive CPU
Product
HPC System
Exascale
SGA 3 SGA4SGA 1&2
EPI ROADMAP
RISC-V accelerator vision @ EPI
• High throughput devices
• Long Vectors (a la Cray? A la Cyber205? ...)
• Decouple Front end - Back end engines
• Optimize memory throughput ([Command vector, 98])
• Explicit locality management (long register file)
• ISA is important
• Decouple/hide again hardware details, reuse SW technologies (compilers, OS,…),
• Specific instructions?
• “limited” number of control flows
• Hierarchical Acceleration
• Nesting
• Low power: ~ low voltage x ~ low frequency
• MPI+OpenMP
• Task based, throughput oriented programming approach
• Malleability in application + Dynamic resource (cores, power, BW) management
• Intelligent runtimes & Runtime Aware Architectures
• Architectural support for the runtime
• Accelerator for ML
• Specialized “non Von-Neumann” compute and data motion engines (neural/stencil)
• Tuned numerical precision
BSC and EPI
• EPI is a H2020 EU funded initiative restricted to the 23 original
partners, selected according to EU rules
• EPI plans considering additional participants in future, provided
resources will become available
• In EPI BSC is the leader of the Accelerator activities and contributor
in the rest of the technical programme, including the Common
Platform
• BSC will promote the EPI agenda within its vast academic network
• BSC is open to additional collaboration outside and within EPI to
anyone in the world interested in producing RISC-V IP in Europe and
especially in Barcelona
• Collaboration with the HPC global vendors will remain a key element
of BSC strategy
• Everybody interested in RISC-V is welcome! Just come and talk to
us…
BSC & The Global IT Industry 2018
BSC is Hiring
BSC is looking for talented and motivated professionals with expertise in
the design and verification of IPs to be integrated into top-level HPC SoC
designs. The immediate responsibilities of this group will be related to
The European Processor Initiative.
Experienced professionals (Engineers
and/or PhD holders) wanted for:
• RTL/Microarchitecture
• Verification
• FPGA Design
Find out more:
https://www.bsc.es/join-
us/job-opportunities/103csrre
Or contact: rrhh@bsc.es
Mare Nostrum RISC-V inauguration 202X
MN-RISC-V
Thank you
Barna April 9th, 2018
mateo@bsc.es

More Related Content

Similar to European Processor Initiative & RISC-V

Barcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de RiquezaBarcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de Riqueza
Facultad de Informática UCM
 
Top500 Slides for June 2014
Top500 Slides for June 2014Top500 Slides for June 2014
Top500 Slides for June 2014
top500
 
¿Es posible construir el Airbus de la Supercomputación en Europa?
¿Es posible construir el Airbus de la Supercomputación en Europa?¿Es posible construir el Airbus de la Supercomputación en Europa?
¿Es posible construir el Airbus de la Supercomputación en Europa?
AMETIC
 
Exascale Update from Hyperion Research
Exascale Update from Hyperion ResearchExascale Update from Hyperion Research
Exascale Update from Hyperion Research
inside-BigData.com
 
Nikravesh big datafeb2013bt
Nikravesh big datafeb2013btNikravesh big datafeb2013bt
Nikravesh big datafeb2013bt
Masoud Nikravesh
 
OpenACC Monthly Highlights - February 2018
OpenACC Monthly Highlights - February 2018OpenACC Monthly Highlights - February 2018
OpenACC Monthly Highlights - February 2018
NVIDIA
 
OpenACC Monthly Highlights: July 2021
OpenACC Monthly Highlights: July  2021OpenACC Monthly Highlights: July  2021
OpenACC Monthly Highlights: July 2021
OpenACC
 
01 From K to Fugaku
01 From K to Fugaku01 From K to Fugaku
01 From K to Fugaku
RCCSRENKEI
 
OpenACC Monthly Highlights: May 2020
OpenACC Monthly Highlights: May 2020OpenACC Monthly Highlights: May 2020
OpenACC Monthly Highlights: May 2020
OpenACC
 
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AIArm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
inside-BigData.com
 
OpenACC Monthly Highlights: February 2022
OpenACC Monthly Highlights: February 2022OpenACC Monthly Highlights: February 2022
OpenACC Monthly Highlights: February 2022
OpenACC
 
CINECA for HCP and e-infrastructures infrastructures
CINECA for HCP and e-infrastructures infrastructuresCINECA for HCP and e-infrastructures infrastructures
CINECA for HCP and e-infrastructures infrastructures
Cineca
 
Exploring the Performance Impact of Virtualization on an HPC Cloud
Exploring the Performance Impact of Virtualization on an HPC CloudExploring the Performance Impact of Virtualization on an HPC Cloud
Exploring the Performance Impact of Virtualization on an HPC Cloud
Ryousei Takano
 
OpenACC Monthly Highlights: January 2021
OpenACC Monthly Highlights: January 2021OpenACC Monthly Highlights: January 2021
OpenACC Monthly Highlights: January 2021
OpenACC
 
Achitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and ExascaleAchitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and Exascale
inside-BigData.com
 
Opportunities of ML-based data analytics in ABCI
Opportunities of ML-based data analytics in ABCIOpportunities of ML-based data analytics in ABCI
Opportunities of ML-based data analytics in ABCI
Ryousei Takano
 
Future Commodity Chip Called CELL for HPC
Future Commodity Chip Called CELL for HPCFuture Commodity Chip Called CELL for HPC
Future Commodity Chip Called CELL for HPC
Slide_N
 
Scaling Green Instrumentation to more than 10 Million Cores
Scaling Green Instrumentation to more than 10 Million CoresScaling Green Instrumentation to more than 10 Million Cores
Scaling Green Instrumentation to more than 10 Million Cores
inside-BigData.com
 
Accelerators at ORNL - Application Readiness, Early Science, and Industry Impact
Accelerators at ORNL - Application Readiness, Early Science, and Industry ImpactAccelerators at ORNL - Application Readiness, Early Science, and Industry Impact
Accelerators at ORNL - Application Readiness, Early Science, and Industry Impact
inside-BigData.com
 
Necesidades de supercomputacion en las empresas españolas
Necesidades de supercomputacion en las empresas españolasNecesidades de supercomputacion en las empresas españolas
Necesidades de supercomputacion en las empresas españolas
Cein
 

Similar to European Processor Initiative & RISC-V (20)

Barcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de RiquezaBarcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de Riqueza
 
Top500 Slides for June 2014
Top500 Slides for June 2014Top500 Slides for June 2014
Top500 Slides for June 2014
 
¿Es posible construir el Airbus de la Supercomputación en Europa?
¿Es posible construir el Airbus de la Supercomputación en Europa?¿Es posible construir el Airbus de la Supercomputación en Europa?
¿Es posible construir el Airbus de la Supercomputación en Europa?
 
Exascale Update from Hyperion Research
Exascale Update from Hyperion ResearchExascale Update from Hyperion Research
Exascale Update from Hyperion Research
 
Nikravesh big datafeb2013bt
Nikravesh big datafeb2013btNikravesh big datafeb2013bt
Nikravesh big datafeb2013bt
 
OpenACC Monthly Highlights - February 2018
OpenACC Monthly Highlights - February 2018OpenACC Monthly Highlights - February 2018
OpenACC Monthly Highlights - February 2018
 
OpenACC Monthly Highlights: July 2021
OpenACC Monthly Highlights: July  2021OpenACC Monthly Highlights: July  2021
OpenACC Monthly Highlights: July 2021
 
01 From K to Fugaku
01 From K to Fugaku01 From K to Fugaku
01 From K to Fugaku
 
OpenACC Monthly Highlights: May 2020
OpenACC Monthly Highlights: May 2020OpenACC Monthly Highlights: May 2020
OpenACC Monthly Highlights: May 2020
 
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AIArm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
Arm A64fx and Post-K: Game-Changing CPU & Supercomputer for HPC, Big Data, & AI
 
OpenACC Monthly Highlights: February 2022
OpenACC Monthly Highlights: February 2022OpenACC Monthly Highlights: February 2022
OpenACC Monthly Highlights: February 2022
 
CINECA for HCP and e-infrastructures infrastructures
CINECA for HCP and e-infrastructures infrastructuresCINECA for HCP and e-infrastructures infrastructures
CINECA for HCP and e-infrastructures infrastructures
 
Exploring the Performance Impact of Virtualization on an HPC Cloud
Exploring the Performance Impact of Virtualization on an HPC CloudExploring the Performance Impact of Virtualization on an HPC Cloud
Exploring the Performance Impact of Virtualization on an HPC Cloud
 
OpenACC Monthly Highlights: January 2021
OpenACC Monthly Highlights: January 2021OpenACC Monthly Highlights: January 2021
OpenACC Monthly Highlights: January 2021
 
Achitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and ExascaleAchitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and Exascale
 
Opportunities of ML-based data analytics in ABCI
Opportunities of ML-based data analytics in ABCIOpportunities of ML-based data analytics in ABCI
Opportunities of ML-based data analytics in ABCI
 
Future Commodity Chip Called CELL for HPC
Future Commodity Chip Called CELL for HPCFuture Commodity Chip Called CELL for HPC
Future Commodity Chip Called CELL for HPC
 
Scaling Green Instrumentation to more than 10 Million Cores
Scaling Green Instrumentation to more than 10 Million CoresScaling Green Instrumentation to more than 10 Million Cores
Scaling Green Instrumentation to more than 10 Million Cores
 
Accelerators at ORNL - Application Readiness, Early Science, and Industry Impact
Accelerators at ORNL - Application Readiness, Early Science, and Industry ImpactAccelerators at ORNL - Application Readiness, Early Science, and Industry Impact
Accelerators at ORNL - Application Readiness, Early Science, and Industry Impact
 
Necesidades de supercomputacion en las empresas españolas
Necesidades de supercomputacion en las empresas españolasNecesidades de supercomputacion en las empresas españolas
Necesidades de supercomputacion en las empresas españolas
 

More from inside-BigData.com

Major Market Shifts in IT
Major Market Shifts in ITMajor Market Shifts in IT
Major Market Shifts in IT
inside-BigData.com
 
Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...
inside-BigData.com
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networks
inside-BigData.com
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
inside-BigData.com
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
inside-BigData.com
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
inside-BigData.com
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networks
inside-BigData.com
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
inside-BigData.com
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecasts
inside-BigData.com
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Update
inside-BigData.com
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19
inside-BigData.com
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuning
inside-BigData.com
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
inside-BigData.com
 
State of ARM-based HPC
State of ARM-based HPCState of ARM-based HPC
State of ARM-based HPC
inside-BigData.com
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Acceleration
inside-BigData.com
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
inside-BigData.com
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Era
inside-BigData.com
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computing
inside-BigData.com
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Cluster
inside-BigData.com
 
Overview of HPC Interconnects
Overview of HPC InterconnectsOverview of HPC Interconnects
Overview of HPC Interconnects
inside-BigData.com
 

More from inside-BigData.com (20)

Major Market Shifts in IT
Major Market Shifts in ITMajor Market Shifts in IT
Major Market Shifts in IT
 
Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networks
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networks
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecasts
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Update
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuning
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
 
State of ARM-based HPC
State of ARM-based HPCState of ARM-based HPC
State of ARM-based HPC
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Acceleration
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Era
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computing
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Cluster
 
Overview of HPC Interconnects
Overview of HPC InterconnectsOverview of HPC Interconnects
Overview of HPC Interconnects
 

Recently uploaded

"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
"Frontline Battles with DDoS: Best practices and Lessons Learned",  Igor Ivaniuk"Frontline Battles with DDoS: Best practices and Lessons Learned",  Igor Ivaniuk
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
Fwdays
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Brandon Minnick, MBA
 
JavaLand 2024: Application Development Green Masterplan
JavaLand 2024: Application Development Green MasterplanJavaLand 2024: Application Development Green Masterplan
JavaLand 2024: Application Development Green Masterplan
Miro Wengner
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Hiroshi SHIBATA
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
saastr
 
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
Jason Yip
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Pitangent Analytics & Technology Solutions Pvt. Ltd
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
saastr
 
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Harnessing the Power of NLP and Knowledge Graphs for Opioid ResearchHarnessing the Power of NLP and Knowledge Graphs for Opioid Research
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Neo4j
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Zilliz
 
"Choosing proper type of scaling", Olena Syrota
"Choosing proper type of scaling", Olena Syrota"Choosing proper type of scaling", Olena Syrota
"Choosing proper type of scaling", Olena Syrota
Fwdays
 
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyFreshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
ScyllaDB
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
saastr
 
GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)
Javier Junquera
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansBiomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Neo4j
 

Recently uploaded (20)

"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
"Frontline Battles with DDoS: Best practices and Lessons Learned",  Igor Ivaniuk"Frontline Battles with DDoS: Best practices and Lessons Learned",  Igor Ivaniuk
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
 
Artificial Intelligence and Electronic Warfare
Artificial Intelligence and Electronic WarfareArtificial Intelligence and Electronic Warfare
Artificial Intelligence and Electronic Warfare
 
JavaLand 2024: Application Development Green Masterplan
JavaLand 2024: Application Development Green MasterplanJavaLand 2024: Application Development Green Masterplan
JavaLand 2024: Application Development Green Masterplan
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
 
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
 
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Harnessing the Power of NLP and Knowledge Graphs for Opioid ResearchHarnessing the Power of NLP and Knowledge Graphs for Opioid Research
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
 
"Choosing proper type of scaling", Olena Syrota
"Choosing proper type of scaling", Olena Syrota"Choosing proper type of scaling", Olena Syrota
"Choosing proper type of scaling", Olena Syrota
 
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyFreshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
 
GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansBiomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
 

European Processor Initiative & RISC-V

  • 1. European Processor Initiative & RISC-V Prof. Mateo Valero BSC Director 9/May/2018 RISC-V Workshop, Barcelona
  • 2. Barcelona Supercomputing Center Centro Nacional de Supercomputación Spanish Government 60% Catalan Government 30% Univ. Politècnica de Catalunya (UPC) 10% BSC-CNS is a consortium that includes BSC-CNS objectives Supercomputing services to Spanish and EU researchers R&D in Computer, Life, Earth and Engineering Sciences PhD programme, technology transfer, public engagement
  • 3. People and Resources Data as of 31st of December 2017
  • 4. Context: The international Exascale challenge • Sustained real life application performances, not just Linpack… • Exascale will not just allow present solutions to run faster, but will enable new solutions not affordable with today HPC technology • From simulation to high predictability for precise medicine, energy, climate change, autonomous driven vehicles… • The International context (US, China, Japan and EU…) • The European HPC programme • The European Processor initiative • BSC role
  • 5. Top5 November 2017 list (compact view) Rank Site Computer Procs Rmax Rpeak Mflops/Watt 1 Wuxi, China Sunway SW26010 260C 10.649.600 93.015 125.436 6.051 2 Guangzhou, China Xeon E5-2692+Phi 3.120.000 33.863 54.902 1.902 2736000 3 CSCS, Switzerland Cray XC50, Xeon E2690 12C+P100 361.760 19.590 25.326 8.622 297920 4 JAMEST, Japan ZettaScaler Xeon D-1571, PEZY-SC2 19860000 19.135 28.192 14.173 19840000 5 DOE/SC/Oak Ridge, US Cray XK7, Opteron 16C+K20 560.640 17.590 27.113 2.143 261632 6 DOE/NNSA/LLNL, US BlueGene/Q, BQC 16C 1.572.864 17.173 20.133 2.177 7 DOE/NNSA/LANL/SNL, US Cray XC40, IXeon Phi 7250 (KNL) 979.968 14.137 43.902 3.678 8 DOE/SC/LBNL/NERSC, US Cray XC40, Xeon Phi 7250 (KNL) 622.336 14.015 27.881 3.558 9 JCA, Japan PRIMERGY, Xeon Phi 7250 (KNL) 556.104 13.555 24.913 4.896 10 Riken/AICS, Japan K computer, SPARC64 705.024 10.510 11.280 830 11 DOE/SC/Argonne, US BlueGene/Q, Power BQC 16C 786.432 8.587 10.066 2.177 12 TACC Texas, US PowerEdge, Xeon Phi 7250 (KNL), 368.928 8.318 18.216 N/A 13 GSIC-TIT, Japan SGI, Xeon E5,Tesla P100 135.828 8.125 12.127 10.258 120736 14 CINECA, Italy Lenovo, Xeon Phi 7250 68C, KNL 314.384 7.471 15.372 N/A 15 UKMET, UK Cray XC40, Xeon E2695 18C 241.920 7.039 8.129 N/A 16 BSC, Spain Lenovo, Xeon Platinum 8160 24C 153.216 6.471 10.296 3.965
  • 6. According to HPL According to HPCG benchmark Top5 Rank Name Country Rmax Rpeak % Efficiency 1 Sunway TaihuLight China 93,015 125,436 74.15 % 2 Tianhe-2 China 33,863 54,902 61.68% 3 Piz Daint Switzerland 19,590 25,326 77.35% 4 Gyoukou Japan 19,135 28,192 67.87% 5 Titan US 17,590 27,113 64.87% 6 Sequoia US 17,173 20,133 85.30% 7 Trinity US 14,137 43,902 32.20% 8 Cori US 14,015 27,881 50.27% 9 Oakforest- PACS Japan 13,555 24,913 54.41% 10 K Computer Japan 10,510 11,280 93.17% Rank Name Rmax Rpeak % Efficiency 1 K Computer 603 11,280 5.34% 2 Tianhe-2 580 54,902 1.06% 3 Trinity 546 43,902 1.24% 4 Piz Daint 486 25,326 1.92% 5 Sunway TaihuLight 481 125,436 0.38% 6 Oakforest- PACS 385 24,913 1.54% 7 Cori 355 27,881 1.27% 8 Sequoia 330 20,133 1.64% 9 Titan 322 27,113 1.19% 10 Mira 167 10,066 1.66%
  • 7. According to HPL According to HPCG benchmark Top5 Rank Name Country Rmax Rpeak % Efficiency 1 Sunway TaihuLight China 93,015 125,436 74.15 % 2 Tianhe-2 China 33,863 54,902 61.68% 3 Piz Daint Switzerland 19,590 25,326 77.35% 4 Gyoukou Japan 19,135 28,192 67.87% 5 Titan US 17,590 27,113 64.87% 6 Sequoia US 17,173 20,133 85.30% 7 Trinity US 14,137 43,902 32.20% 8 Cori US 14,015 27,881 50.27% 9 Oakforest- PACS Japan 13,555 24,913 54.41% 10 K Computer Japan 10,510 11,280 93.17% 16 Mare nostrum Spain 6,471 10,296 62,85% Rank Name Rmax Rpeak % Efficiency 1 K Computer 603 11,280 5.34% 2 Tianhe-2 580 54,902 1.06% 3 Trinity 546 43,902 1.24% 4 Piz Daint 486 25,326 1.92% 5 Sunway TaihuLight 481 125,436 0.38% 6 Oakforest- PACS 385 24,913 1.54% 7 Cori 355 27,881 1.27% 8 Sequoia 330 20,133 1.64% 9 Titan 322 27,113 1.19% 10 Mira 167 10,066 1.66% 15 Mare Nostrum 122 10,296 1,18%
  • 8. Rank Previous rank Machine Country Number of cores GTEPS 1 1 K computer Japan 663,552 38,621 2 2 Sunway TaihuLight China 10,599,680 23,755 3 3 DOE/NNSA/LLNL Sequoia USA 1,572,864 23,751 4 4 DOE/SC/Argonne National Laboratory Mira USA 786,432 14,982 5 5 JUQUEEN Germany 262,144 5,848 6 new ALCF Mira - 8192 partition United States 131,072 4,212 7 6 ALCF Mira - 8192 partition USA 131,072 3,556 8 7 Fermi Italy 131,072 2,567 9 new ALCF Mira - 4096 partition United States 65,536 2,348 10 8 Tianhe-2 (MilkyWay-2) China 196,608 2,061 8 Graph500
  • 9. Rank TOP500 Rank System Cores Rmax (TFlop/s) Power (kW) Power Efficiency (GFlops/watts) 1 259 Shoubu system B - PEZY Computing RIKEN -Japan 794,400 842.0 50 16.84 2 307 Suiren2 - PEZY Computing KEK -Japan 762,624 788.2 47 16.77 3 276 Sakura - PEZY Computing PEZY Computing K.K. -Japan 794,400 824.7 50 16.49 4 149 DGX SaturnV Volta - NVIDIA Tesla V100 NVIDIA Corporation -United States 22,440 1,070.0 97 11.03 5 4 Gyoukou - PEZY-SC2 700Mhz Japan 19,860,000 19,135.8 1,350 14.17 6 13 TSUBAME3.0 - NVIDIA Tesla P100 SXM2 Japan 135,828 8,125.0 792 10.26 7 195 AIST AI Cloud - NVIDIA Tesla P100 SXM2 Japan 23,400 961.0 76 12.64 8 419 RAIDEN GPU subsystem - NVIDIA Tesla P100 Japan 11,712 635.1 60 10.59 9 115 Wilkes-2 - NVIDIA Tesla P100 University of Cambridge - United Kingdom 21,240 1,193.0 114 10.46 10 3 Piz Daint - NVIDIA Tesla P100 Switzerland 361,760 19,590.0 2,272 8.62 33 16 MareNostrum- Lenovo SD530 Barcelona Supercomputing Center Spain 153,216 6,470.8 1,632 3.97 9 Green500
  • 10. Application processor performance MN3-MN4 Application Cores Performance WRF 256 1.37 128 1.06 GROMACS 1024 192 1.19 NAMD 2048 1.31 1024 1.17 728 1.25 512 1.20 VASP 64 2.2 32 2.0 HPL 96 2.24 48 2.21
  • 11. From MN3 to MN4
  • 12. MareNostrum4 Total peak performance: 13,7 Pflops General Purpose Cluster: 11.15 Pflops (1.07.2017) CTE1-P9+Volta: 1.57 Pflops (1.03.2018) CTE2-Arm V8: 0.5 Pflops (????) CTE3-KNH?: 0.5 Pflops (????) MareNostrum 1 2004 – 42,3 Tflops 1st Europe / 4th World New technologies MareNostrum 2 2006 – 94,2 Tflops 1st Europe / 5th World New technologies MareNostrum 3 2012 – 1,1 Pflops 12th Europe / 36th World MareNostrum 4 2017 – 11,1 Pflops 2nd Europe / 13th World New technologies
  • 13. Worldwide HPC roadmaps From Tianhe-2.. …to Tianhe-2A with domestic technology. From K computer… … to Post K with domestic technology. From the PPP for HPC… to future PRACE systems… …with domestic technology with domestic technology. IPCEI on HPC ?
  • 14. US launched RFP for Exascale (April 2018) • To develop at least two new exascale supercomputers for the DOE at a cost of up to $1.8 billion • The deployment timeline for these new systems begins in the third quarter of 2021, with ORNL’s exascale supercomputer, followed by a third quarter 2022 system installation at LLNL. The ANL addition or upgrade, if it happens, will also take place in the third quarter of 2022. • The new systems can’t exceed 40 MW, with the preferred power draw in the 20 to 30 MW (including exascale, counting storage, cooling and any other auxiliary equipment ) • The other critical requirement is that the ORNL and ANL systems are architecturally diverse from one other • Proposals are due in May, the bidders will be selected before the end of the Q2 • Each system is expected to cost between $400 to $600 million second quarter.
  • 15. Worldwide HPC roadmaps From Tianhe-2.. …to Tianhe-2A with domestic technology. From K computer… … to Post K with domestic technology. From the PPP for HPC… to future PRACE systems… …with domestic technology with domestic technology. IPCEI on HPC ?
  • 16. EU HPC Ecosystem • Specifications of exascale prototypes • Technological options for future systems • Identify applications for co- design of exascale systems • Innovative methods and algorithms for extreme parallelism of traditional & emerging applications • Collaboration of HPC Supercomputing Centres and application CoEs • Provision of HPC capabilities and expertise Centers of Excellence in HPC applications
  • 17. HPC Ecosystem EXDCI Eurolab-4-HPC ExCAPE GreenFLASH READEX ESCAPE INTERTWINE ALLScale ANTAREX ExaFLOW ComPat NLAFET ExaHYPE NEXTGenIO SAGE ExaNEST ExaNoDe ECOSCALE EXTRA Mont-Blanc 3 Mango HPC R&D: H2020 current landscape BioExcel COEGSS EoCoE E-CAM ESiWACE MAX NOMAD PoP Centres of Excellence Biomolecular Global systems Energy Simulation Modelling Weather Climate Materials Performance optimisation Computational Biomedicine CompBioMed FET & e-Infra Calls WP2014-2015
  • 18. 18 A big challenge, and a huge opportunity for Europe 18 Extend current mobile chips with the needed HPC features – Explore the use vector architectures in mobile accelerators (vector processor ARM-based, 15+ Teraflops chip, 150 watts)… unique opportunity for Europe – One design for all market segments: mobile, data centers, supercomputers 2011 2012 2013 2014 2015 2016 2017 256 nodes 250 GFLOPS 1.7 Kwatt 120 TFLOPS 80 Kwatt 200 PFLOPS ~10 MWatt Built with the best of the market Built with the best that is coming What is the best that we could do? GFLOPS/W Integrated ARM + GPU
  • 19. Mont-Blanc HPC Stack for ARM Industrial applications System software Hardware Applications
  • 20. World Top 20 machines (status November 2017) Europe has only 4 machines in world top 20 ■ Italy (CINECA) – Nr 14 ■ UK (Meteorological office) – Nr 15 ■ Spain (BSC, Barcelona) – Nr 16 ■ Germany (HLRS, Stuttgart) – Nr 19 EU not in HPC world leaders
  • 21. BSC and the European Commission Final plenary panel at ICT - Innovate, Connect, Transform conference, 22 October 2015 Lisbon, Portugal. The transformational impact of excellent science in research and innovation
  • 22. Paris, 27 October 2015 European Commission President Jean-Claude Juncker "Our ambition is for Europe to become one of the top 3 world leaders in high-performance computing by 2020" The European Commission and HPC Vice-President Andrus Ansip "I encourage even more EU countries to engage in this ambitious endeavour" • Ministers from seven MS (France, Germany, Italy, Luxembourg, Netherlands, Portugal and Spain) sign a declaration to support the next generation of computing and data infrastructures Digital Day Rome, 23 March 2017
  • 23. The EuroHPC Declaration Declaration signed in Rome, March 23rd, 2017 by: Agree to work towards the establishment of a cooperation framework - EuroHPC - for acquiring and deploying an integrated exascale supercomputing infrastructure that will be available across the EU for scientific communities as well as public and private partners France Germany Italy Luxembourg Netherlands Portugal Spain Belgium Slovenia Bulgaria Switzerland Greece Croatia Six more countries signed the Declaration:
  • 24. EuroHPC latest news: Europa portail: (January 2018) http://europa.eu/rapid/press-release_IP-18-64_en.htm
  • 25. FET 2014-2017 HW/SW building blocks and co-design 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 l l l l l l l l ll pre-exascale HPC Ecosystem development FET 2020: extreme scale HPC systems and applications exascale FET 2019: extreme scale computing & data for key applications LEIT-ICT 2017-2020: Framework Programme Agreement (FPA) Low-power/Microprocessor HPC LEIT-ICT 2018: Extreme Scale Demonstrators Technology & Applications development integration in co-design procurement Widening access and services LEIT-ICT 2018: HPC / Big Data enabled Large-scale Test-beds and Applications HPC timeline in H2020 LEIT/FET (indicative)
  • 26. EPI 23 partners, from research to industry from consortium to EU high tech fabless EU - FPA Semiconductor EPI Common Platform Fabless company Industrial hand of EPI Incorporated by a couple EPI members and external investors 1st EPI production
  • 27. Three streams General purpose and Common Platform • ARM SVE or other candidates… • BULL: System integrator  chip integrator Accelerator • RISC-V • EU design: BSC, CEA, Chalmers, ETHZ, EXTOLL, E4, FORTH, Fraunhofer, IST, UNIBO, UNIZG, Semidynamics Automotive • Infineon, BMW…
  • 28. 2018 2019 2020 2021 2022 2023 2024 2025 CPU? ACCEL. HPC System PreExascale HPC Chip & system Accel. Chip & system Core Technolog y KeyMarkets HPC Chip & system Accel. Chip & system Gen 1 Gen 2 HPCCARS Automotive CPU Proof of Concept Gen 3 Automotive CPU Product HPC System Exascale SGA 3 SGA4SGA 1&2 EPI ROADMAP
  • 29. RISC-V accelerator vision @ EPI • High throughput devices • Long Vectors (a la Cray? A la Cyber205? ...) • Decouple Front end - Back end engines • Optimize memory throughput ([Command vector, 98]) • Explicit locality management (long register file) • ISA is important • Decouple/hide again hardware details, reuse SW technologies (compilers, OS,…), • Specific instructions? • “limited” number of control flows • Hierarchical Acceleration • Nesting • Low power: ~ low voltage x ~ low frequency • MPI+OpenMP • Task based, throughput oriented programming approach • Malleability in application + Dynamic resource (cores, power, BW) management • Intelligent runtimes & Runtime Aware Architectures • Architectural support for the runtime • Accelerator for ML • Specialized “non Von-Neumann” compute and data motion engines (neural/stencil) • Tuned numerical precision
  • 30. BSC and EPI • EPI is a H2020 EU funded initiative restricted to the 23 original partners, selected according to EU rules • EPI plans considering additional participants in future, provided resources will become available • In EPI BSC is the leader of the Accelerator activities and contributor in the rest of the technical programme, including the Common Platform • BSC will promote the EPI agenda within its vast academic network • BSC is open to additional collaboration outside and within EPI to anyone in the world interested in producing RISC-V IP in Europe and especially in Barcelona • Collaboration with the HPC global vendors will remain a key element of BSC strategy • Everybody interested in RISC-V is welcome! Just come and talk to us…
  • 31. BSC & The Global IT Industry 2018
  • 32. BSC is Hiring BSC is looking for talented and motivated professionals with expertise in the design and verification of IPs to be integrated into top-level HPC SoC designs. The immediate responsibilities of this group will be related to The European Processor Initiative. Experienced professionals (Engineers and/or PhD holders) wanted for: • RTL/Microarchitecture • Verification • FPGA Design Find out more: https://www.bsc.es/join- us/job-opportunities/103csrre Or contact: rrhh@bsc.es
  • 33. Mare Nostrum RISC-V inauguration 202X MN-RISC-V
  • 34. Thank you Barna April 9th, 2018 mateo@bsc.es