This document discusses the potential for an open software platform for the Square Kilometre Array (SKA) radio telescope project. It notes the "data deluge" problem and sees the SKA Science Data Processor (SDP) compute model as a general case for distributed computing. It introduces TOPS, an open source distributed operating system being developed by Open Parallel for rack-scale computing. The document advocates starting with open source and OpenStack and asks for help developing an open software stack to address exascale challenges like power consumption, heterogeneous hardware, and software-defined systems.

1. An Open Software Platform
for the SKA?
Nicolás Erdödy
Founder, CEO – Open Parallel Ltd
SKA in Seoul:
Asia-Pacific Regional Workshop in HI Science
Seoul, Korea - November 2, 2015

3. Brief
● The Problem: “data deluge”
● The Opportunity: We see the SKA SDP
compute model as the general case
● TOPS - A Distributed OS for Rack Scale
Computing.
● How to start: Open Source & Open Stack
● We need your help...

4. Efficient recognition of signals
from a massive amount
of data noise
improves operational efficiencies,
scientific discovery and
forms the cradle of
adaptive service delivery.

5. As today's HPC
becomes tomorrow's
Cloud computing platform
it will enable a wider application of
Machine Understanding
-the near real-time
complex modelling
and analysis of data
that leads to insight
and faster decisions.

7. Today's problems and beyond
● Non-professional software development (in
many scientific environments) lead to limited or
null software stack reuse.
● Data deluge (44 ZettaBytes by 2020 – IDC).
● The exascale challenge: 10^18 calculations p/s
● Power consumption.
● Heterogeneous hardware.
● Compute Islands?
● Software Defined Everything (SDN, SDI, SDS).

8. SDP Preliminary Compute Platform
Design (*)
● Quite different than on a general-purpose
supercomputer
● Workload-driven system design philosophy to
tune SDP hardware.
● SDP Compute Islands - “self-contained,
independent collection of compute nodes”.
● Only process data contained in the island itself.
● (*) Broekema, van Nieuwpoort, Bal (July 2015)

9. TOPS – What are we doing
● Conceived as a Rack Scale distributed
Operating System for the Data Centre.
● TOPS workshop #2 (Multicore World 2016, Wellington, NZ)
● CSP's Software Development Plan.
● Panel “Towards an Open Software Stack for
Exascale Computing” at SuperComputing15 – Austin,
Texas, USA (15-20 Nov).
● OpenStack - South Africa - 2015 CHPC conference,
Pretoria (1-4 Dec)

10. “Towards an Open Software Stack for
Exascale Computing” (SC15 – 19Nov – Austin, USA ).
● Prof. Jack Dongarra (Tennessee, Turing Fellow –
Manchester, scientific advisory board for SKA, LINPACK).
● Prof. Thomas Sterling (Indiana, Centre for Research
Extreme Scale Technologies, Beowulf clusters, MCW15).
● Dr. Pete Beckman (Exascale Technology & Computing
Institute, Argonne Labs – Chicago, Argo OS).
● Dr. John Gustafson (fmr AMD Chief Product Architect,
Director Intel Labs, Sun, Gustafson's Law, MCW14).
● Dr. Robert Wisniewski (Chief Software Architect Exascale
Computing, Intel -formerly Chief Software Architect Blue
Gene Supercomputer, IBM).
● Chris Broekema (SDP COMP Task Leader, ASTRON,
Netherlands).

11. Your input
● What should TOPS be / do for you?
● Let's start a chat -this is a 2-5 years
conversation.
● Thank you!
● OpenParallel.com
● MulticoreWorld.com
● Nicolas.Erdody@openparallel.com
● Oamaru, South Island, New Zealand

12. The data deluge will change
how we build and manage
new systems to store
and understand data

13. “This time, we have time”
a) How should software evolve to address exascale demands? Are OpenStack
or other platforms part of the solution? Algorithms should evolve, and most
legacy software will be replaced: so what should be the focus of the new ones?
To save power? To increase speed? To improve programmability?
b) How heterogeneous would/should “your” exascale system be? Is there a role
for Co-design towards exascale?
c) The SKA project is an example where once it becomes operational, exascale
problems will appear very early. But venture capitalists don't invest in radio-
telescopes. What killer app would attract them towards early adoption of
exascale computing? Which industries will migrate first?
d) Would HPC in the cloud be possible for exascale computing? Which
technologies do we need to change / challenge to make it feasible? Data
transport? Servers? What are those technologies most important for your work?
e) Do you envisage a similar development effort as we had with OSS over
decades, or will bottlenecks develop due to lack of specialised talent globally?
Will proprietary solutions continue to emerge or co-exist? Who will “own” the
exascale era? Microsoft? Google? Will there be competition between existing
companies and “not yet founded” start-ups, or will each organisation have its
own in-house development shop?

14. Open Parallel Ltd.
● NZ Company – involved with SKA since 2011.
● 3 NZ organisations (AUT, VUW & OP) were
formally pre-selected in 2012 by the NZ Govt
-after international peer-review, as viable
prospects for engagement in SDP and CSP.
● Since 2013 Open Parallel is formally:
- Work Package Manager of the Software
Development Environment for the CSP,
- Contributing to SDP Compute Platform,
- Member of the NZ SKA Alliance (lead by AUT
university).

15. OP's work for the SKA
What's done (2013 - 2015)
Version 1 of “SKA CSP Element Software Development Plan”
(SE-23). How the CSP element “will develop and deliver software
and/or firmware in accordance to a design specification.”
Incorporated into SDP’s Architecture Reference Document (2014)
and referenced in SDP’s “Compute Platform: Software stack
developments and considerations” (SDP’s PDR 2015).
To be fully delivered over Stage 2 timeframe (2015 - 2017).
Most recent task: provide CSP Consortium with SW/FW process
requirements to support the effective re-use of SW and FW
developed during pre- construction for construction.
Note:
CSP = Central Signal Processor
SDP = Science Data Processor

16. Could SKA's IT be a Black Swan?
• “Black Swan” = high-impact events that are rare and
unpredictable but in retrospect seem not so
improbable.
• One in six IT projects (is) a black swan, with a cost
overrun of 200%, on average (*).
• Developers struggle to combine different software
systems.
• 61% of managers report major conflicts between
project and line organisations.
• (*) “Why your IT Project may be riskier than you think”. B.
Flyvbjerg et al. HBR, Sept. 2011.

17. What is the SKA?
● The world's largest radio telescope
● The ultimate big data project
● The largest supercomputer in the world
● A technological management challenge
and...
● The general case of future HPC + Cloud...

18. Our world is full of data
● “Every year we collect more data than the
rest of the data collected since the
beginning of the Mankind”
(Prof. Alex Szalay, Johns Hopkins University. TEDx
Caltech 2011 – Keynote at Multicore World 2016).
● Exponentially faster computing + successive
generations of inexpensive sensors + you on
your smartphone sharing all those images.
● Data intensive science, synthesizing theory
(equations), experiments and computation with
analytics → new way of thinking is required!

19. “80 percent of success is showing up”
(Woody Allen)