Marco Aldinucci Dipartimento di Informatica, Università of Torino - LE PIATTAFORME AI-ON-DEMAND
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LE PIATTAFORME AI-ON-DEMAND
COME FATTORE DI INNOVAZIONE NELLE PMI
Marco Aldinucci
Dipartimento di Informatica, Università of Torino
fortissimo2 1
OUTLINE
• Motivations
• HPC4AI vision
• Cloud federation + Artificial Intelligence + BigData Analytics
• HPC4AI: A one-stop-shop for AI and BDA
• Data + Processes + Performance
• Novel blockchain-based federated accounting structure
• The universities, the PMIs and the Innovation
BRAIN DRAIN: HIGHEST OUTBOUND/
INBOUND RATIO IN SCIENTIFIC RESEARCHERS
Inbound
Outbound
Hannah Yan Han, “Analyse the migration of scientific researchers”. Toward Data Science, 2018 https://towardsdatascience.com/analyse-the-migration-of-scientific-researchers-5184a9500615
MOTIVATIONS
MOTIVATIONS: AI/BDA SERVICES ARE OPERATED BY MICROSOFT, AMAZON, ETC.
• Proprietary solutions produce lock-in. And continue to exact a rent
• The long-tail of this rental economy model increases inequalities [J.E. Stiglitz]
• AI require GPUs/TPUs. Their cost is high in commercial clouds
• Buying-vs-renting break-even point occurs very early for AI
• AI and BDA need annotated datasets that require human effort for curation
• Local availability of these dataset is an enabling feature for training/analysis
• Datasets contain sensitive information, they should be stored appropriately
• Compliant with European regulations (including privacy, e.g. GDPR) if within EU borders
Possible Arm Cisco IBM NVidia E4Engineering Loquendo Consoft
Partners
BlueReply CSP AizoOn O.R.S. Reply Exemplar NetValue Celi LabInf
Comau FCA Leonardo Prima Industrie General Motors IREN TIM
Intesa SanPaolo Reale Mutua Banca Sella TopIX TorinoWireless INRiM SITI
AI-in-demand platform
Technological Collegio Città Salute ISI IIT Human
GARR INFN-TO ISMB
Partners Carlo Alberto e Scienza Foundation Genova Technopole
Universities, Informatics ICxT HPC Control and
Facts
Departments, Innovation
• INFRA-P call Nov. 2017
UNITO Center Computer
and Economy POLITO Engineering
(coord)
Inter- MEDHIUM
departmental
Centers Philosophy
Digital Media
SmartData Electronics and • Ranked 1st on ~30
Telecom
Maths Law
C3S Scientific
Computing
Center
Engineering submitted projects
Data Centers C3S PdF SmartData HPC
• Kick-off mid apr 2018
• 4.5M€ funding
• 2 partners
Hardware
free experimental
Federated cloud islands
experimental
free • 8 associated partners
cooling GARR cloud “Piemonte zone” cooling
islands
• Coord. M. Aldinucci
islands
(non federated) (non federated)
• Many industrial
National/EU INDIGO GARR
Networks DataCloud
DEEP-HybridDataCloud
INFN-TO national network cloud bursting
Amazon
Azure, etc stakeholders
for research
HPC4AI: THE TURIN’S CENTRE ON HIGH-PERFORMANCE COMPUTING FOR
ARTIFICIAL INTELLIGENCE
• Facilitate scientific research and engineering in the areas of
Artificial Intelligence and Big Data Analytics
• Support large scale experimentation of applications
• Engage regional industry in joint research projects, also boosting their R&D
capabilities
• Gather and store dataset with specific local/EU value (medical, business, code, …)
• Focusing on methods for the on-demand provisioning of AI and
BDA cloud services
HPC4AI: A ONE-STOP-SHOP FOR AI AND BDA
• On-demand Services - Exploitation through cloud abstractions to target different users
• Vertical: Rapidly prototyping + possibly to move the solution down for tuning/optimisation
• Horizontal: Marketplace+ federation at each levels of solutions and data
• Data - to store data & datasets
• Securely, preserving ownership, always available
• Processes - to develop new protocols
• Cross-pollinating computer science, other sciences and engineering
• Automation and continuous improvement of processes
• Performance - to ease the access to HPC
• For Machine Learning and BigData on-demand
Users Kind of service Services Artifacts
Domain experts with no skills on ML and Service-as-a- SaaS for ML and BDA Market place for ML and BDA
BDA. Service (SaaS) designed within HPC4AI services: Dashboards, trained
partners models in several domains (NLP,
Training set not required. Off-the-shelf Vision, …)
algorithms/networks.
Domain experts skilled on ML and BDA. Platform-as-a- PaaS solutions for ML and Market place of VMs and
Not expert in parallel computing. Service (PaaS) BDA directly designed within Platforms realising software
HPC4AI or companion stacks for ML and BDA. Solutions
New networks or pipelines; training set projects for data ingestion, data lake, etc.
required.
Researchers, cloud engineering, ML and BDA 1) Infrastructure- 1) GARR/other cloud able to 1) Openstack, docker, VM, object
framework designers, cloud engineers, stack as-a-Service (IaaS) support federation storage, file storage, kubernetes,
and automation designers. etc.
2) Metal-as-a-
Service (IaaS) 2) Job scheduler for HPC 2) Alternative cloud, job queue,
resources Big Data Stack (Spark, …).
Researchers, run-time designers. Hardware Bare Metal Multicore, GPU, storage, network,
switch, UPS, cooling, etc.
IaaS PaaS
EXAMPLE PAAS ON BARE METAL: KUBERNETES-AS-A-SERVICE
MANAGEMENT OF FEDERATED MARKETPLACE WITH BLOCKCHAIN
Researchers Marketplace
services &
datasets
BlueReply CSP AizoOn
Projects
Legal entities UNITO POLITO Comau FCA Leonardo
Intesa SanPaolo Reale Mutua
hpc4ai
HPC4AI coins
cryptocurrency
hpc4ai free exchanger
coins
Data Centers C3S PdF SmartData HPC
hpc4ai blockchainEXAMPLE: NEXT GENERATION DATA MANAGEMENT FOR LIFE SCIENCE
1. Start from existing data
• Store, share, sell: under the full control of owner
2. Imagine AI support
• For scoring, support and automation - not for diagnosis
3. Evaluate annotation, improve the processes
• Imagine how to improve protocols/processes and annotation to be better automatised and AI-
supported
4. Develop novel analysis techniques and GoTo 3
• Continuous improving of processes by cross-pollinating computer and life scienceTHE BURNOUT OF ITALIAN RESEARCH ECOSYSTEM
• Italy has no universities in the top 100, good/excellent
groups are patchily spread across different universities
• Italian universities are becoming a selection machinery of
intelligent youngsters to be sent to foreign PhD and
research centres
• Industry is sliding toward assessed technologies and
becoming progressively unable to innovateWHY ITALIAN UNIVERSITIES ARE BECOMING A SELECTION MACHINERY OF
INTELLIGENT YOUNGSTERS TO BE SENT TO FOREIGN PHD AND RESEARCH CENTRES?
• Con la cultura non si mangia [GT]
• Mandare il curriculum? Meglio giocare a calcetto [GP]
• Volevo vincere il Premio Nobel per l'Economia. Ero anche bravo, ero... non dico lì lì per farlo, però ero
nella giusta... ha prevalso il mio amore per la politica, ed il Premio Nobel non lo vincerò più anche se ho
buone possibilità di diventare presidente della repubblica [RB]
• Cara studentessa, io, da padre le consiglio di cercare di sposare il figlio di Berlusconi o qualcun altro del
genere; e credo che, con il suo sorriso, se lo può certamente permettere [SB]
• In Italia i fondi per la ricerca non sono più bassi, a livello pubblico, della media europea [MR]
• Alla costruzione del tunnel tra il Cern ed i laboratori del Gran Sasso, attraverso il quale si è svolto
l'esperimento, l'Italia ha contribuito con uno stanziamento oggi stimabile intorno ai 45 milioni di euro
[MSG]HPC4AI & THE BURNOUT
• HP4AI is primarily a modern, large research laboratory
• We don’t provide production computing, we don’t compete with Amazon, Cineca, etc.
• We are interested to experiment new solutions at different layers in the stack of cloud
abstractions, and to create a protocol to move them between different layers (i.e. a
software engineering methodology)
• We want to keep, develop and transfer to our students and
industrial partners the knowledge
• On how to create, manage, develop, innovate with the cloud/HPC/AI/BDA
• We will not use any technology without fully understand itBUSINESS PLAN
PREVIOUS PROJECTS ON PARALLEL COMPUTING @UNITO
THE LAST 8 YEARS
• Infrastructure
• HPC4AI (POR-FESR 2014-2020): Turin’s centre in High-Performance Computing for Artificial Intelligence
(2018, 24 months, total cost 4.5M €).
• C3S: Competence Center on Scientific Computing (Compagnia di San Paolo, founding 900K €).
• Research
• OptiBike (EU I4MS): Robust Lightweight Composite Bicycle design and optimisation, experiment of EU i4MS Fortissimo2 project (2017, 24 months, total cost 230K €).
• Toreador (EC-RIA, H2020, ICT-2015-16): TrustwOrthy model-awaRE Analytics Data platfORm (2015, 36 months, total cost 6.2M €).
• Rephrase (EC-RIA, H2020, ICT-2014-1): Refactoring Parallel Heterogeneous Resource-Aware Applications – a Software Engineering Approach (2015, 36 months, total cost
3.5M €).
• REPARA (EC-STREP, 7th FP): Reengineering and Enabling Performance And poweR of Applications (2013, 36 months, total cost 3.5M €).
• IMPACT (founded by Compagnia di San Paolo): Innovative Methods for Particle Colliders at the Terascale (2012, 36 months).
• ParaPhrase (EC-STREP, 7th FP): Parallel Patterns for Adaptive Heterogeneous Multicore Systems (2011, 42 months, total cost 4.2M €).
• Networking
• HiPEAC (EC-NoE, 7th FP & H2020) European Network of Excellence on High Performance and Embedded Architecture and Compilation (2012-now).
• cHiPSet (EC-COST Action IC1406): High-Performance Modelling and Simulation for Big Data Applications (2015, 48 months).
• NESUS (EC-COST Action IC1305): Network for Sustainable Ultrascale Computing (2014, 48 months).
• DIMA-HUB (EU I4MS): Regional Digital Manufacturing Innovation Hub (2016, 6 months).EuroPar 2018
Co-chairs: M. Aldinucci, L. Padovani, M. Torquati
Torino, Italy — 27-31 August 2018You can also read
