a user-centric vision for future einfrastructure and services in norway hans a. eide, phd group...

A user-centric vision for future eInfrastructure and services in Norway

Hans A. Eide, PhDGroup leaderResearch Computing ServicesUSIT, University of Oslo

eSOP seminar on eInfrastructure Use Roadmap, March 11, 2011

University of Oslo and IT, research, HPC

• Two-tier IT organization:– Local: (at institutes / faculties)

– Central: University Center for Information Technology (USIT)

• USIT

– 240+ FTE and growing

– Covers all aspects of University IT activities

• Section for Education and Research Support (SUF)

– Provides resources, tools, support, competence for the primary production (education and research), 40 FTE

• Research Computing Services (VD – the HPC group)

– Research support, competence, operations

Research Computing Services group

• 14 people, 9 with research background (Ph.D)– “buffer” between advanced resources and researchers

– Advanced user support (e.g. parallelization, grid enabling)

– Computation, storage, visualization, emerging tech.

– Not limited to “hard sciences” or HPC

• Multi-source funding

– RCN (Notur, NorStore, Norgrid, projects)

– Research projects (life sci., astro, physics, etc.)

– UiO

• Training, support, operations, help-desk

Tomorrow’s eInfrastructure and services

Tomorrow’s eInfrastructure and services• Must support all fields of research, be accessible• Help maximize science production, to the benefit of

society (social, economic, ..), while• minimizing TCO (i.e. be effective)• Environmentally friendly• Quickly adapt to technology changes and new

demands to give competitive edge• Maintained at a sufficient and stable level relative to

use/need

Usually divided in two aspects:•eInfrastructure

– Hardwarei.e. computing resources, storage, network, …

•Services– Software– Brainware (support services)

eInfrastructure really should mean the whole package, but

eInfrastructure

The eInfrastructure pyramid(anno 2011)

PRACEMulti-Petaflop

Petaflop

Nordic?

Sub-Petaflop

Development Competence Services Support

Training Portals Tools Databases Data sourcesGreen(?)

Greener

Greenest

Capacity Capability

WLCG

NGIs

clou

ds

Today’s situation (simplified) for computing and storage

Basic infrastructure (network)

UiTNTNUUiBUiO

Today’s situation (simplified) for computing and storage

Basic infrastructure (network)

UiTNTNUUiBUiO

End of 2010 300kW (maxed out)From 2011 900kW (sufficient to 2013+)Limited space (and cooling)

Infinite power, space, and cooling

Alternative 1: go alone (x MW in 2015)

UiO+

UiO

Greendatacenter

Alternative 2: together (y MW in 2015+)

UiTNTNUUiBUiO

GreendatacenterGreen

datacenterGreendatacenter

+

Alternative 3 (2020!)

15

UiOUiOUiOUiO

UiOUiOUiOUiOU of XU of X

UiOUiOUiOUiOUiOUiOU of YU of Y

UiOUiOUiOUiO

UiOUiOUiOUiO

UiOUiOUiOUiO

U of YU of Y

Green datacenterGreen datacenter

“Life science”

Green datacenterGreen datacenter

“Climate”Green datacenterGreen datacenter

“Particle physics”

UiOUiOUiOUiO

UiOUiOU of XU of X

Green datacenterGreen datacenter

“Language technology”

Services

Ideal eInfrastructure services:• National core services together with local services

– Fully financed, permanent positions– Close to local resources, users– Pool of competence (advanced user support)– Training, courses, outreach, marketing– Technology watch, early adopters– Partake in Nordic/EU/world-wide programs– Members who are experienced with ICT in the research

process (have background as researchers)

The four waves of extraordinary growth in use of ICT

Mechanicalcalculator

19461820 1968

Towards thecomputer

1991A tool for many

A tool for “all”

2010

Data systemseverywhere

Research and developmentResearch and development

Mainframe computers

PC (affordable)

Internet applications

Advanced services and infrastructures

Number of users

(inverse of skills needed by users)

The evolution of the HPC computing pyramid (William Gropp, UIUC)

21.04.23 19

High Performance Workstations

Mid-Range Parallel Processors and Networked Workstations

Center Supercomputers

Tera Flop Class

Laptops, phones, wristwatches, eye glasses…

Single Cabinet PetascaleSystems

(or attack of the killer GPU successors)

Center Exascale Supercomputers

1993 2029

www.zettaflops.org

Users needed to be “inside the box” Users “outside the box”

Tomorrow’s today’s (average) user• Knows little (nothing) about HPC (and have no interest

in it either)• Most can’t program (at least not good)• Don’t want to spend time learning something if it can

be avoided• Just want results and move on• Doesn’t know what is available• ..but expects to get services, resources, and support

for free

SUIT 2010 – UiO user survey

SUIT 2010 – Research support

12) Bruker du, eller kjenner du til følgende tjenester fra USIT?Bruker / Har brukt / Kjenner til / Kjenner ikke til / Ikke aktuelt

Challenges

• Even HPC for dummies is too advanced(and why should users bother?)

• Knowledge about basic methodology seem to be declining in all fields, among students and researchers alike (e.g. statistics, mathematics)

• Hard to reach the “customers” with passive marketing (i.e. web-pages)

• Late adopters of new technologies/capabilities (“don’t ask me what I need, you should tell me what I need”)

• Serial jobs (not necessarily embarrassingly parallel)

(Some) solutions

• Make it simple to useF.ex. computing portals (can mitigate problem of serial jobs by e.g. using GPUs w/o user even knowing!)

• Emphasis on using ICT methods and eInfrastructure in the education program – part of the curriculum!

• Tailored courses and training for user groups• Forward-leaning marketing of services (e.g. approach

and ask “why are you not using our xyz service in your research?”)

• Advanced support (enter early in the problem formulation/design process), competence

40+ applications

Example: Bioportal

• 2659 registered users, 700+ active• 40+ applications (MrBayes, RaXML, BLAST, Paup, structure, R,

BEAST og PhyML, …)

• Bio (life science), chemistry, statistics• Tailored 454 sequencing work-flow• Use nearly 3 mill CPU hrs. in 6 mo.• Pre-compiled binaries allow advanced optimizations,

e.g. use of GPUs and MPI, transparently to the users

ICT services for hum-soc• Qualitative methods

– Used extensively in humanities and social sciences– Rich media (audio, video)– Typical applications: NVIVO, HyperResearch, Transana

• Quantitative methods– Statistics– Potentially huge datasets– Sometimes sensitive data– Typical applications: STATA, SPSS, R

• Storage services (data intensive)• Big need for training

eInfrastructure and services for sensitive data• Sensitive data enters in many fields

– Life Science– Medicine– Psychology– Social studies– Pedagogic studies

• Lack of eInfrastructure and services for sensitive research data impairs ability to perform research

DNA-sequencingDNA-sequencing

QuestionnairesQuestionnaires

Video/audioVideo/audio

MRIMRI

Patient/clinicalPatient/clinical

GeneticsGenetics

Industrial Industrial researchresearch

Sensitive research dataSensitive research data

eInfrastructure and services in the future– This is the missing slide about clouds and virtualization

Thanks for your attention!

Questions