HPCwire: Twins Separated at Birth: Cloud Computing, HPC and How Microsoft Is Trying To Change How We Think About Scale

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March 12, 2009

Twins Separated at Birth: Cloud Computing, HPC and How Microsoft Is Trying To Change How We Think About Scale

by John West, for HPCwire

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When Dan Reed joined Microsoft in late 2007, his writings and public appearances made it clear that he hadn't totally abandoned HPC -- on his blog he continued to feature issues important to our community. But in the stream of posts on everything from the rise of multicore processors to national science policy, he never said exactly what he was doing at Microsoft. I assumed he was doing something related to Windows HPC Server or the entry of Microsoft in the HPC market, but then why was he in the research group? Perhaps a new product.

We found out on Feb. 24 when Rick Rashid, the senior vice president of Microsoft Research, unveiled the Cloud Computing Futures (CCF) organization at TechFest, and pointed to Reed as its director.

The CCF complements Microsoft's production cloud services, named "Windows Azure," announced in late October of last year, but in a broader sense is aiming to transform the way we build and manage very large-scale computational resources. As Reed writes on his blog, he came to run the CCF to answer the challenge of constructing a reliable, purpose-built cloud infrastructure, one not cobbled together from parts built for other tasks:

Imagine a world where heterogeneous multicore processors are design and optimized for diverse workloads, where solid state storage changes our historical notions of latency and bandwidth, where on-chip optics, system interconnects and LAN/WAN networking simplify data movement, where scalable systems are resilient to component failures, where programming abstractions facilitate functional dispersion across devices and facilities, where new applications are developed more quickly and efficiently. This can be.

But as he points out, we have a long way to go to get to this future from where we are today:

If we built utility power plants the same way we build cloud infrastructure, we would start by visiting The Home Depot and buying millions of gasoline-powered generators. This must change.

Much of the press around the CCF announcement has been about the server research agenda, and CCF demonstrations at TechFest showed off low power, low footprint, cloud compute clusters built from netbook processors (like the Intel Atom; you might recall that SGI also showed an experimental Atom-based server at SC08) along with innovative power and capacity management software. Next-generation storage and memory, new processor architectures, networks, and programming models are all also on the table as part of the CCF research agenda.

At its core, cloud computing is about building (and managing) computationally-based services at a very large scale, and so it shares some of the basic issues that have motivated the supercomputing community for decades. But, other than scale, do HPC and the cloud have anything in common? What does HPC bring to the table from its comparatively long history that will be important as cloud infrastructure becomes an industry and research area of its own? HPCwire talked to Dr. Reed by email, and he shared some of his thoughts about the intersection of cloud computing and HPC.

HPCwire: What is the big picture view of the CCF?

Dr. Reed: The CCF story is about approaching cloud computing infrastructure as an integrated design problem, looking at the balance of support infrastructure, computing hardware and software, not only at a single site but across an international network of interconnected sites. The scale and scope of the problem means that some of our traditional design assumptions no longer hold, particularly if we want to enable a new class of applications.

Based on my background in high-performance computing, I believe clouds open exciting possibilities to rethink computational science and address some of the problems we face. We have successfully leveraged commodity hardware to create large clusters, but at considerable cost. Cluster programming remains difficult at scale. We have turned a generation of researchers into parallel programmers and system administrators; institutions are struggling with rising demands for machine space, power and cooling; and duplicated facilities make sharing expertise and data difficult. I helped make many of those things happen, so I feel some responsibility to help us find a new path.

The specific aspect relative to HPC is that cloud services are game changers, just as commodity clusters were a decade ago and graphics accelerators have been recently. This is not the future, this is the present.

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