Designing a Modular DSP Core For Real-Time Audio Performance
Co-designing Modular
Transcript of Co-designing Modular
Estela Suarez (JSC)20.11.2019 – SC19, BoF
Co-designing Modular Supercomputing
The Research leading to these results has received funding from the European Commission's FP7 and H2020 Programmes, under Grant Agreements n° 287530, 610476, and 754304.
Modular Supercomputing
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• E. Suarez*, N. Eicker, Th. Lippert, "Modular Supercomputing
Architecture: from idea to production", Chapter 9 in Contemporary
High Performance Computing: from Petascale toward Exascale,
Volume 3, pp 223-251, CRC Press. (2019)
• E. Suarez*, N. Eicker, and Th. Lippert, "Supercomputer Evolution at
JSC", Proceedings of the 2018 NIC Symposium, Vol.49, p.1-12,
(2018) [online: http://juser.fz-juelich.de/record/844072].
Composability of heterogeneous resources
• Cost-efficient scaling
• Orchestration software
• Fit application diversity
– Large-scale simulations
– Data analytics
– Machine- and Deep Learning
– Artificial Intelligence
Module 2
Booster
BN
BN
BN
BN
BN BN
BN
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Module 1
Cluster
CN
CN
CN
CN
Module 6
Multi-tier
Storage
System
Storage system
Storage system
Module 3
Data Analytics
Module
AN AN AN
Module 5
Quantum
Module
QN QNModule 4
Neuromorphic
Module
NN NN
High-scale simulation
Deep Learningworkflow
Data Analyticsworkflow
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DEEP-EST Prototype
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HW and SW co-designed with Applications
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Applications drive HW+SW developments
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DLMOS
xPic GMM
So
urc
e: F
ZJ
xPic – Space Weather
Application on a Modular Supercomputer
DLMOS
Infe-rence
DPP
Training
xPicField
Solver Particle Solver
GMM
GMM
xPic: 35% gain (in 8 nodes)
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The DEEP projects have received funding from the European Union’s Seventh Framework Programme (FP7) for research, technological development and demonstration and the Horion2020 (H2020) funding framework under grant agreement no. FP7-ICT-287530 (DEEP), FP7-ICT-610476 (DEEP-ER) and H2020-FETHPC-754304 (DEEP-EST).
www.deep-projects.eu
@DEEPprojects