On Ten Year Trends - Parallel Goes Mainstream

Several bloggers have been discussing the current "ten year trends" that are transforming the computing environment, including Cloud Computing, Virtualization, Flash, and Mobility.

However, there is a deeper trend that while well underway, is so significant that it is often overlooked. That is the forced transition to loosely coupled distributed computing models caused by the knee in increasing compute performance by making individual processors faster.

Over the next five years, I believe we are going to see a full-fledged transition in hardware systems from tightly coupled single and multi-processor shared memory systems to loosely coupled many-processor systems that communicate via message passing. This trend is already evident in the high-performance computing space, where having hit the limits of individual processor performance, then having hit the limits of shared memory, virtually all new architectures have adopted this approach.

One of the fundamental drivers of this transition is a new economic model that measures computing power per dollar, or computing power per watt. This model favours many smaller less powerful processors over fewer high-power processors. After all, with Atom and ARM processors costing only a few dollars per core in volume, and performing around the same as a 1 GHz Pentium did just a few years ago, with a fraction of the power and heat dissipation, I predict we will soon see a transition to inexpensive servers where one or two rack units are crammed full of hundreds to thousands of these class of processors, all connected together by what looks like a Ethernet fabric.

The timing is right — Microsoft's talking about it, IBM's already done it, and the mobile market has brought the component volumes up to the point where the economics are right.

But five years does not make a ten-year trend: The larger change is that to programming models, languages and mindsets. Very few people in the industry can work comfortably and productively in massively parallel environments, as we have seen in the difficulty in building scalable web-based systems like Twitter. Computer Science still teaches programming and computer architecture around the old model of the "one true core", with parallel and distributed programming taught as a speciality, often at the graduate studies level.

It is going to take five or more years for these new massively parallel hardware and ways of thinking to filter down to the next generation of programmers who can think parallel, create new tools, libraries and stacks, and then play tens to hundreds of thousands of nodes like an instrument.

Imagine having a hundred thousand cores on your desktop. Imagine having ten million of them in your data centre. The problems are significant, and exciting.

Blades for Storage

Over the last decade, I've had a significant interest in the benefits of blade server architectures. In early 2000, I worked on a development project that used CompactPCI cards from ZiaTech (later acquired by Intel) where we used the CompactPCI bus as a high-performance low-latency system-to-system interconnect. Several years later, we also evaluated blade systems from IBM and HP to see if we could leverage some of the benefits of blade systems for StorageGRID deployments. But, at every point, there were major downsides, namely, cost, bandwidth and storage interconnectivity.

Thus, until now, I've never found a product that provides the storage connectivity that allows a blade system to complete economically with DAS attached shelves linked to 1U servers. That changed this week, with IBM announcing the new BladeCenter S Chassis.

Enabling Features of the BladeCenter S

There are three features in this product that allow it to be a perfect foundation for software-based storage systems:

Feature #1 - SAS/SATA RAID modules, which allow you to hang up to eight SAS/SATA shelves off each BladeCenter chassis. With 12 TB of SATA storage per shelf, that allows you to have 96 TB of raw addressable storage per BladeCenter. This feature is unique to the IBM offering at this time, and is the key enabling feature of the product for storage software solutions.

Feature #2 - Internal SAS/SATA storage, with two bays, each holding 6 3.5" drives (up to 6 TB SATA, 3 TB SAS). This is perfect for system and database disks, and allows all of the control storage to be co-located with the compute blades.

Feature #3 - 10GigE switch modules and blade NICs give you the bandwidth you need to provide high-performance storage services to external clients without bottlenecks.

Scalable Hardware for Storage Software

With the BladeCenter chassis starting at less than $2,500, this allows a common architecture and hardware platform that extends from entry-level systems consisting of two HA blades with internal storage all the way up to multi-chassis systems managing hundreds of terabytes of storage. This also reduces support costs, as you can leverage a common pool of replacement parts.

The blade architecture allows the compute hardware to be field replaceable, which reduces MTTR. And as the attached storage is assignable across blades, there is the possibility to design a system that has a hot standby blade that dynamically reassigns the storage associated with the failed blade, and resumes providing services.

If I were to design a new software storage product, this would be the foundation hardware I would choose. The software would run in VMs, granted, but this hardware finally provides the cost/performance/supportability tradeoffs that I view are critical for such a product to succeed, and provides sufficient built-in storage to allow a common hardware platform to extend down to entry-level systems.