Finding a Competitive Advantage with High Performance Computing

High Performance Computing (HPC), or supercomputing, is a critical enabling capability for many industries, including energy, aerospace, automotive, manufacturing, and more. However, one of the most important aspects of HPC is that HPC is not only an enabler, it is often also a differentiator – a fundamental means of gaining a competitive advantage.

Differentiating with HPC

Differentiating (gaining a competitive advantage) through HPC can include:

• faster - complete calculations in a shorter time;
• more - complete more computations in a given amount of time;
• better - undertake more complex computations;
• cheaper - deliver computations at a lower cost;
• confidence - increase the confidence in the results of the computations; and 
• impact - effectively exploiting the results of the computations in the business.

These are all powerful business benefits, enabling quicker and better decision making, reducing the cost of business operations, better understanding risk, supporting safety, etc.

Strategic delivery choices are the broad decisions about how to do/use HPC within an organization. This might include:

• choosing between cloud computing and traditional in-house HPC systems (or points on a spectrum between these two extremes);
• selecting between a cost-driven hardware philosophy and a capability-driven hardware philosophy;
• deciding on a balance of internal capability and externally acquired capability;
• choices on the balance of investment across hardware, software, people and processes.

The answers to these strategic choices will depend on the environment (market landscape, other players, etc.), how and where you want to navigate that environment, and why. This is an area where our consulting customers benefit from our expertise and experience. If I were to extract a core piece of advice from those many consulting projects, it would be: "explicitly make a decision rather than drift into one, and document the reasons, risk accepted, and stakeholder buy-in".

Which HPC technology?

A key means of differentiating with HPC, and one of the most visible, is through the choice of hardware technologies used and at what scale. The HPC market is currently enjoying (or is it suffering?) a broader range of credible hardware technology options than the previous few years.

HPC Getting More Choices - Technology Diversity

HPC has been easy for a while ...

When buying new workstations or personal computers, it is easy to adopt the simple mantra that a newer processor or higher clock frequency means your application will run faster. It is not totally true, but it works well enough. However, with High Performance Computing, HPC, it is more complicated.

HPC works by using parallel computing – the use of many computing elements together. The nature of these computing elements, how they are combined, the hardware and software ecosystems around them, and the challenges for the programmer and user vary significantly – between products and across time. Since HPC works by bringing together many technology elements, the interaction between those elements becomes as important as the elements themselves.

Whilst there has always been a variety of HPC technology solutions, there has been a strong degree of technical similarity of the majority of HPC systems in the last decade or so. This has meant that (i) code portability between platforms has been relatively easy to achieve and (ii) attention to on-node memory bandwidth (including cache optimization) and inter-node scaling aspects would get you a long way towards a single code base that performs well on many platforms.

Increase in HPC technology diversity

However, there is a marked trend of an increase in diversity of technology options over the last few years, with all signs that this is set to continue for the next few years. This includes breaking the near-ubiquity of Intel Xeon processors, the use of many-core processors for the compute elements, increasing complexity (and choice) of the data storage (memory) and movement (interconnect) hierarchies of HPC systems, new choices in software layers, new processor architectures, etc.

This means that unless your code is adjusted to effectively exploit the architecture of your HPC system, your code may not run faster at all on the newer system.

It also means HPC clusters proving themselves where custom supercomputers might have previously been the only option, and custom supercomputers delivering value where commodity clusters might have previously been the default.

SC17 Tutorials - HPC cost models, investment cases and acquisitions

Following our successful HPC tutorials at SC16 and OGHPC17, I'm delighted to report that we've had three tutorials accepted for SC17 in Denver this November, all continuing our mission to provide HPC training opportunities for HPC people other than just programmers.

At SC17, we will be delivering these three tutorials:

• [Sun 12th, am] "Essential HPC Finance: Total Cost of Ownership (TCO), Internal Funding, and Cost-Recovery Models"
• [Sun 12th, pm] "Extracting Value from HPC: Business Cases, Planning, and Investment"
• [Mon 13th, am] "HPC Acquisition and Commissioning"

In a last minute bit of co-ordination, Sharan Kalwani will be following these with his related tutorial "Data Center Design" on Mon 13th pm.

Are these tutorials any good?

The HPC procurement tutorial was successfully presented at SC13 (>100 attendees) and SC16 (~60 attendees). Feedback from the SC16 attendees was very positive: scored 4.6/5 overall and scored 2.9/3 for “recommend to a colleague”.

The HPC finance tutorial was successfully presented at SC17 (~60 attendees) and at the Rice Oil & Gas HPC conference 2017 (~30 attendees). Feedback from the SC16 attendees was very positive: scored 4.3/5 overall and scored 2.7/3 for “recommend to a colleague”.

The HPC business case tutorial is new for SC17.

What is the goal of the tutorials?

The tutorials provide an impartial, practical, non-sales focused guide to the business aspects of HPC facilities and services (including cloud), such as total cost of ownership, funding models, showing value and securing investing in HPC, and the process of purchasing and deploying a HPC system. All tutorials include exploration of the main issues, pros and cons of differing approaches, practical tips, hard-earned experience and potential pitfalls.

What is in the tutorials?

Essential HPC Finance Practice: Total Cost of Ownership (TCO), Internal Funding, and Cost-Recovery Models

• Calculating and using TCO models
• Pros and cons of different internal cost recovery and funding models
• Updated from the SC16 base, with increased consideration of cloud vs in-house HPC

Extracting Value from HPC: Business Cases, Planning, and Investment

• Applicable to either a first investment or an upgrade of existing capability
• Most relevant to organizations with a clear purpose (e.g., industry) or those with a clear service mission (e.g., academic HPC facilities)
• Identifying the value, building a business case, engaging stakeholders, securing funding, requirements capture, market survey, strategic choices, and more

HPC Acquisition and Commissioning

• Procurement process including RFP
• Specify what you want, yet enable the suppliers to provide innovative solutions beyond the specification both in technology and in the price
• Bid evaluation, benchmarks, clarification processes
• Demonstrate to stakeholders that the solution selected is best value for money
• Contracting, project management, commissioning, acceptance testing

Who are the tutors?

Me (Andrew Jones, @hpcnotes), Owen Thomas (Red Oak Consulting), and Terry Hewitt. We have been involved in numerous major HPC procurements and other strategic HPC projects since 1990, as service managers, bidders to funding agencies, as customers and as impartial advisors. We are all from the UK but have worked around the world and the tutorials will be applicable to HPC projects and procurements anywhere. The tutorials are based on experiences across a diverse set of real world cases in various countries, in private and public sectors.

What if you need even more depth?

These SC17 tutorials will deliver a lot of content in each half day. However, if you need more depth, or a fuller range of topics, or are looking for a CV step towards becoming a future HPC manager, then our joint TACC-NAG summer training institute is the right thing for you: "Where will future HPC leaders come from?"



Hope to see you at one (or more!) of our tutorials at SC17 this November in Denver.
@hpcnotes

Is cloud inevitable for HPC?

In 2009, I wrote this article for HPC Wire: "2009-2019: A Look Back on a Decade of Supercomputing", pretending to look back on supercomputing between 2009 and 2019 from the perspective of beyond 2020.

The article opens with the idea that owning your own supercomputer was a thing of the past:

"As we turn the decade into the 2020s, we take a nostalgic look back at the last ten years of supercomputing. It’s amazing to think how much has changed in that time. Many of our older readers will recall how things were before the official Planetary Supercomputing Facilities at Shanghai, Oak Ridge and Saclay were established. Strange as it may seem now, each country — in fact, each university or company — had its own supercomputer!"

I got this bit wrong:

"And then the critical step — businesses and researchers finally understood that their competitive asset was the capabilities of their modelling software and user expertise — not the hardware itself. Successful businesses rushed to establish a lead over their competitors by investing in their modelling capability — especially robustness (getting trustable predictions/analysis), scalability (being able to process much larger datasets than before) and performance (driving down time to solutions)."

Hardware still matters - in some cases - as a means of gaining a competitive advantage in performance or cost [We help advise if that is true for our HPC consulting customers, and how to ensure the operational and strategic advantage is measured and optimized].

And, of course, my predicted rush to invest in software and people hasn't quite happened yet.

Towards the end, I predicted three major computing providers, from which most people got their HPC needs:

"We have now left the housing and daily care of the hardware to the specialists. The volume of public and private demand has set the scene for strong HPC provision into the future. We have the three official global providers to ensure consumer choice, with its competitive benefits, but few enough providers to underpin their business cases for the most capable possible HPC infrastructure."

Whilst my predictions were a little off in timing, some could be argued to have come true e.g., the rise to the top of Chinese supercomputing, the increasing likelihood of using someone else's supercomputer rather than buying your own (even if we still call it cloud), etc.

With the ongoing debate around cloud vs in-house HPC (where I am desperately trying to inject some impartial debate to balance the relentless and brash cloud marketing), re-visiting this article made an interesting trip down memory lane for me. I hope you might enjoy it too.

As I recently posted on LinkedIn:

"Cloud will never be the right solution for everyone/every use case. Cloud is rightly the default now for corporate IT, hosted applications, etc. But, this cloud-for-everything is unfortunately, wrongly, extrapolated to specialist computing (e.g.,  high performance computing, HPC), where cloud won't be the default for a long time.

For many HPC users, cloud is becoming a viable path to HPC, and very soon perhaps even the default option for many use cases. But, cloud is not yet, and probably never will be, the right solution for everyone. There will always be those who can legitimately justify a specialized capability (e.g., a dedicated HPC facility) rather than a commodity solution (i.e., cloud, even "HPC cloud"). The reasons for this might include better performance, specific operational constraints, lower TCO, etc. that only specialized facilities can deliver. 

The trick is to get an unbiased view for your specific situation, and you should be aware that most of the commentators on cloud are trying to sell cloud solutions or related services, so are not giving you impartial advice!"

[We provide that impartial advice on cloud, measuring performance, TCO, and related topics to our HPC consulting customers]


@hpcnotes