HPC Innovator’s Work Spans Two Continents

By Nicole Hemsoth

May 28, 2010

Over the past two decades, Dr. Ashwini Nanda has been at the center of some of the most cutting-edge HPC projects and initiatives in the world.  At IBM’s T.J. Watson Research Center, in New York, Dr. Nanda led the development of the Cell processor-based  systems (QS20, QS21, and QS22 blades) and software technologies for high performance computing. That work culminated in the construction of the Roadrunner supercomputer for Los Alamos National Laboratory. Later, as the head of Computational Research Laboratories (CRL) in Pune, India, he directed the development of the “Eka” HPC cluster that, in 2007, held the title of Asia’s fastest supercomputer. He also established the shared memory systems group at IBM Research, worked on the Amazon superscalar architecture at Texas Instruments, and developed parallel computers for India’s missile defense systems at Wipro, Bangalore.

Recently he moved back to India, where he founded HPC Links, a company that offers parallel programming software tools and services for the global high performance computing community. We got the opportunity to ask Dr. Nanda about how he sees the HPC industry today, how it’s changing, and what led him to start up his company.

HPCwire: Maybe we can start with some of your thoughts about the development of high performance computing in India. What are the principal challenges in building the country’s HPC capability? And how do you see the way forward for HPC and supercomputing in India — for both vendors and users?
 
Ashwini Nanda: India has less than 1 percent of the compute power in the global TOP500 supercomputing list today. This tiny share of the pie is not indicative of the financial and high-tech might of India. The gap indicates there is significant room for growth in HPC infrastructure in the country. The gap one sees today is perhaps due to the lack of broad awareness of the benefits of HPC to scientific/technical research and to business enterprises. This is despite the commendable progress made by organizations such as CDAC, CRL, SERC/IISc and HiPC in spreading HPC awareness in the country.

India’s per capita spending in high performance computing is negligible compared to the US, Japan and Germany, and for that matter compared even to China, Spain and Russia. The Unique ID (Adhaar) project of the government will likely fuel growth in HPC related to data mining, consummer security and national security. The government has procured quite a few HPC clusters for weather and climate prediction which would foster research and application development in these areas. India has very successful government enterprises in nuclear energy, space and defence, which would benefit tremendously from the use of HPC. The US counterparts in these sectors are the prime movers of the HPC industry there. The Indian government has the financial strength and must spend heavily in HPC in order to make these sectors globally competitive.
 
India has vibrant pharmaceutical, financial, entertainment and manufacturing industries, all of whom would gain significant productivity and competitiveness by using HPC. We built the Eka machine at CRL soley with private investment from Tata. The other industrial powerhouses in India have the financial means, and they will likely follow suit once they see the benefits of HPC to their business. Talking to leaders from government, academia and industry across the country, one can sense a growing awareness of the potential of HPC, which I believe will translate into a faster pace of growth in HPC infrastructure and services during the next five years or so in India. When that happens, it will benefit the multinational vendors as well as the local vendors.

HPCwire: What do you think will be the role of cloud computing for HPC users in India?

Nanda: Culturally, and economically, reuse and sharing of resources are well accepted in the Indian society. Once the users discover the utility of HPC, I think sharing resources through cloud platforms will come naturally to them, especially the small and medium scale users of HPC. But more importantly, India could also become a key global host of cloud computing infrastructure and services due to attractive low-cost operations and highly skilled technical manpower.

HPCwire: You had a rather prominent role in the development of Cell processor-based systems and software at IBM. The Cell helped usher in the petaflop era, but overall it looks like the impact of this technology in supercomputing is going to be relatively limited. What do you think the Cell brought to the HPC space and what lessons were learned?

Nanda: The Cell based systems from IBM made two important contributions to HPC technology, besides helping cross the petaflop barrier. First they set the new trend of using hybrid multicore clusters — with CPU-GPU combinations — to build the most cost-effective, power-efficient and best-performing supercomputers. Secondly, creating a software ecosystem to harness the compute power of a revolutionary processor like Cell seemed prohibitive in the beginning. But the Cell systems effort at IBM Research showed that an effective collaboration of government, academia and industry can indeed build a respectable software ecosystem for a new architecture.

It’s true that the momentum around Cell has has been lost, but credit should go to IBM for laying the foundations of a new era that would see the proliferation of hybrid multicore CPU-GPU combination clusters in solving key HPC problems. We are already seeing glimpses of this through the momentum building around such offerings from AMD, Intel and NVIDIA.

HPCwire: In HPC, which hardware and software technologies do you see becoming increasing important over the next, say, five years?

Nanda: I believe in terms of hardware, hybrid multicore GPU-CPU combination technologies and commodity InfiniBand and Ethernet technologies will continue to lead the way and take us through the exaflop mark. In terms of software we will see more emphasis being put on tools that make it easier to write parallel applications and increase productivity.

HPCwire: Switching to your current role as the founder and CEO of HPC Links: What is the company about and what was your motivation to launch this as a business?

Nanda: While doing the systems work at IBM and at Tata over the last few years, the obvious realization came to me that now the commoditization of HPC platforms is complete. We have been building affordable parallel machines all around the world, and almost any one who needs access to a parallel machine can access one today. But are these machines utilized well enough? Not really. Are most people, or industries, who could benefit from HPC, taking advantage of these platforms today? The answer is clearly no. So what is the problem? The US government Council on Competitiveness identified two years back that there are three primary barriers to mass adoption of HPC. Namely, lack of parallel programming skills, lack of parallel applications, and high cost of adoption.

HPC Links was formed last year to help address these customer pain points. Our goal is to help businesses stay competitive by alleviating these pain points and achieving high efficiency, faster time to market and enhanced product quality through innovative use of HPC, cloud and multicore solutions. We are addressing all the three key barriers in HPC adoption through our parallel application services offerings, system integration offerings and the software tools and packages under development.

HPCwire: What is unique about the company?
 
Nanda: Our uniqueness today, if I can point to the most significant one, is our interdisciplinary skill pool. We have Ph.D.’s and Masters in multitude of scientific and engineering disciplines, all adept at various flavors of parallel programming, on all kinds of hardware and software platforms. Mix that with the breadth of domain knowledge the HPC Links team has across industry verticals, and you get a really unique, comprehensive parallel programming skill pool in the world.

HPCwire: What do you see as the principal challenges in developing parallel applications for science and technical computing codes today?

Nanda: The hard challenges in parallel application development as I see are lack of skills, and productive tools. Tackling the challenge of productive tools for parallel programming, I believe, will take longer than tackling the issue of lack of skills. There is the general lack of parallel programmers in the world today, which the universities have started to address pretty effectively. And then there is the problem that people who are good in parallel programming are not necessarily trained in various application domains, and people who are domain experts are often times not proficient in parallel programming. The key is to bring domain experts and parallel programmers together and cross train them on the job.

HPCwire: Who do think will be your main customers for these services?

Nanda: In the near term we see majority of our customers outside of India where the HPC market has higher momentum and awareness — especially in the US and Europe. The Indian HPC market is in its nascent stage, but has great potential in the longer term. Our services are targeted toward any one who can benefit from an experienced parallel programming skill pool in research and development, scaling, testing and optimization of parallel applications in a wide range of domains. For example, recently we signed up with Microsoft to provide this kind of parallel application programming services for their HPC Server platform. This makes our services available to the Windows HPC Server users and ISVs in all industry segments. We have deep Linux cluster programming expertise, and are working with universities and national labs, as well as industry HPC users.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last week the cloud giant released deeplearn.js as part of that in Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Spoiler Alert: Glimpse Next Week’s Solar Eclipse Via Simulation from TACC, SDSC, and NASA

August 17, 2017

Can’t wait to see next week’s solar eclipse? You can at least catch glimpses of what scientists expect it will look like. A team from Predictive Science Inc. (PSI), based in San Diego, working with Stampede2 at the Read more…

By John Russell

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Leading Solution Providers

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This