Techno Musings

I’ve been intentionally planting seeds across several posts for sometime now.  Specifically, I’ve been trying to set the stage about pointing out the relatively static nature of general purpose processors versus the dynamic nature of hardware accelerated software on FPGAs.  I also know that by talking about this in this way, I’m pushing ahead of where customers are thinking.  It is my opinion that the architectures I’ve been describing set the stage for building in real automation that the body of enterprise users have been questing for.  As I’ve also lived through and run design sessions with users and I want to relate a point: lots of automation is requested, but when asked about implementation time frames and if they trust the automation, there is well hesitation on both fronts.  Users like automation, but couched as tangible usability improvements or on a roadmap, but the message is clear: users always want to be in control while reaping the benefits from the force multiplication effect — one person can do the job of two to three people. What I’m going to talk about is meant to set the stage for creating infrastructures and architectures can can provide real automation not hyper usability, however, I fully recognize that this is not something that will not happen in short order.

For many years, since my university days really, I’ve been a fan of borrowing themes from the natural world for the realm of computer science and engineering.  One constant phenomena available in the natural world is the dance between the environment and the organisms which live in concert with the environment.  Basically as one changes, the other changes in response, forcing a change in the originator of the first change, and the cycle continues on and on. It is like dancing where the leader and the follower move synchronously with one another making something of beauty.  Because of the relatively slow rate of change in general purpose processors we will consider them as the environment while software in a computer system we will think of as the organism.  Today the organism, software, is forced into an unnatural rate of change and further the software cannot see, at least in its short execution time, the environment/hardware change in response its activities.  However through raising things like interrupts the hardware can lead the software to perform certain activities or trigger call-backs, etc.  I guess this is more like dancing whilst standing on top of someone’s feet, in that the software really doesn’t have the freedom or flexibility to push back as a peer partner in the dance. What I am getting at is that there is a key missing piece in most modern systems allowing the software to exist as a full partner to the hardware changing the behavior or configuration of the hardware and participating fully in being changed by the hardware.  In short the dance!

Again, hybrid computing devices can answer the call, and yes I expect my esteemed colleagues to chafe under this point.  Hybrid computing systems offer fixed computing elements (think ASICs and General Purpose CPUs) and flexible computing elements (think FPGAs).  With the combination it is possible to contemplate software that can react to the hardware and push on the hardware to change and optimize configurations for the task at hand.  For those that understand neural networks which evolve the best approach to the problem being worked, augmenting static hardware with FPGAs would be a natural extension of the neural network approach, but the system should, in theory, be able to achieve improved speed and I would argue emergent properties. In this way the software is dancing with the hardware and each is changing to meet the other. With the notion of neural networks there is the human brain and all and within the human brain there are elements like the medulla oblongata which is basically hard wired to handle autonomic functions and is much like an ASIC in that it cannot change configuration and it is absolutely required for life to function.  However the cerebral cortex is literally changing its physical nature as we learn so again the natural world provides an example of what is possible.  As I talked about in a previous post, some of the skills that can be brought into muscle memory like typing get stuck into deep parts of our brain so that we don’t have to think about actually doing them.  I imagine that this model could be the source of the automation perhaps learned by traditional software through neural network techniques and then offloaded to FPGAs and hardware accelerated software which can emerge new autonomic behaviors, and voila. (Yeah I know I really need that PowerPoint compiler right about now, this is the automation I was talking about.)

In the long term, like say in the next 10 years or more, I believe that in the storage and processing space we will see the continued adoption of hybrid computing architectures.  Further I would expect to see software that can best take advantage of these hybrid systems.  The combination of the software and hardware will evolve and dance together so that it can solve key problems better than merely a static hardware software combination alone.  The system will learn to solve problems offload key learned algorithms, accelerate application I/O, figure out the right placement of LBAs, etc.

By the way the selection of Hitachi’s technologies already are hybrid in nature.  We include FPGAs, general purpose CPUs, and ASICs in our systems already.  Again we do a lot of things under the covers that I cannot discuss on this forum, but let’s just say that we are advancing the cause quietly and carefully.

P.S.  I had originally intended to span this over several posts, but as I kept going preserving the integrity of the concept and line of thinking is key.  So hopefully you Mr. Reader have hung in until the end.

P.P.S.  Here is a collection of companies, groups and consortiums who are also building hybrid computing systems with FPGAs.  I reference them because I want people to understand that this is not just unique to Hitachi it is a phenomenon, enjoy.

1. XtremeData - … XtremeData’s key IP comes in the form of innovative hardware components (FPGA-based In-Socket Accelerators™) coupled to an extensive software and firmware stack.  … In 2005, strong market demand steered XtremeData into productizing and selling the FPGA In-Socket Accelerators™ – originally intended only for in-house use. …  Our intent is to continue on this path: enabling our customers in financial services, video imaging, military, medical, and bioinformatics to create their own hardware-accelerated appliances.
2. Netezza - Today, Netezza is the data warehouse appliance leader, combining storage, processing, database and analytics into a single system that delivers 10-100x the performance, at half the cost and one-third the power of other approaches. Think of it as a Ferrari, with the price and efficiency of an economy car.
3. Exegy - The hardware-acceleration technology behind the Exegy Ticker Plant provides a competitive edge to the high frequency, colocated trader who requires a ticker plant …
4. Nallatech - For over 15 years, Nallatech has been at the forefront of technological and market innovation in FPGA computing in the Embedded Defense and High Performance Computing markets.
5. FHPCA - The FPGA High Performance Computing Alliance (FHPCA) is developing high-performance computing solutions using Field Programmable Gate Arrays(FPGAs) to deliver new levels of performance into the technical computing market.
6. Altera’s Consortium for FPGA based HPC - Altera Corporation (Nasdaq: ALTR) today announced the development of a new university program to support academic research into high-performance computing. AMD, Sun Microsystems and XtremeData are participating in the program that will donate $1 million in workstations and development software to universities. Using the workstations, participating universities will be able to research and drive the adoption of FPGA co-processing for high-performance computing applications such as medical imaging, data analytics, text searches, network security, bioinformatics and energy.