Biomolecular device using self-assembled DNA nanostructures?

Posted by Cameron Hughes, Tracey Hughes @ 12:18:AM | October 30, 2009

As I sit at my computer with it multicores considering the advantages of parallelism, faster computers, better performance, a strange feeling comes over me, 'Haven't I heard this before?'

We are constantly inundated with the idea of 'better performance' or 'the most current' whether it be a computer, a complier, an operating system, a library, a development tool, or whatever, there is always a promise of something better, something current, something that will speed up the development process.

As a professional you must increase your skill level to accommodate it, 'what is the learning curve for that new complier, that new API, development environment, operating system and of course all of those cores just setting there with nothing to process, I must find a way to utilize them'. It is demanding being a professional, you can't lag behind this stuff. So we search for help, tools, and workshops and conferences to bring us up to speed in a hurry. You know 'got to meet those deadlines, and it would be great if I had some new mojo to throw in that system so I can get better performance'.


A few decades ago a similar problem was described:

“Since its early days, most research in computer science was concerned in one way or another with two problems:

1. Computers are too slow
2. Programmers are too slow”

That was stated 22 years ago by Ehud Shapiro in his book Concurrent Prolog Volume 1. This is a book of collected papers on, yep you guessed it, research related to ICOT. Will we just continue to develop new computers and then beat ourselves up trying to use them? And I mean just use them, let alone use them efficiently. How can we keep this up! How practical is it to get on top of these new technologies with the approach of attending a workshop, reading a book, reading a blog? What about truly radical stuff. What about new paradigms of computing, what happens when they become mainstream.

Well, what's coming down the pike, atomic, molecular and quantum computing? Some are 'non-silicon-based'. Some extend von Neumann architecture, others are radically non-von. Now what? They will require new programming models, new algorithms and new languages. They are not intended to replace silicon-based computers. They maybe better but better when used for certain domains and applications. Considering the state of the contract programming, one way to survive it may be to become an 'expert' in programming using one of the new upcoming paradigms. But how in the world do you become an expert in programming a 'biomolecular device using self-assembled DNA nanostructures'? I am waiting for that workshop!

This Week's Multicore Reading List
MATLAB and Google App Engine
Logging In C++ : Part 2
 Improving log granularity
A Conversation with BitMagic's Developer
Prefer Structured Lifetimes: Local, Nested, Bounded, Deterministic

All Feature Stories

Real World Parallelism Webinar Series

  • November 17, 2009
    Visual Effects for Animation - presented by DreamWorks Animation
    Speaker: Ron Henderson (Bio)

    Ron Henderson manages the FX Tools group at DreamWorks Animation, where he is responsible for developing physical simulation and procedural modeling tools. These systems have been used for key visual effects in recent films such as Kung Fu Panda and Monsters vs. Aliens (March 2009).

    Prior to joining DreamWorks in 2002 he was a senior scientist at Caltech with a joint appointment to the Applied Math and Aeronautics departments, where he worked on efficient techniques for the direct numerical simulation of fluid turbulence.

    Abstract:
    In this webinar, Ron Henderson will show examples of visual effects, from hair and feathers to smoke and fire, from a variety of DreamWorks Animation feature films. He will discuss in general terms the kinds of techniques used to achieve particular visual effects. Finally, Henderson will show a detailed breakdown of the dam-breaking scene from Madagascar: Escape 2 Africa, demonstrating how different elements of key frame animation, simulation, and rendering are combined in a real production shot.

  • December 1, 2009
    A Quick and Easy Way to Parallelize a Legacy Codebase with Intel® Threading Building Blocks (TBBs)
    Speaker: Bernard Laberge, Avid, Senior Principal Engineer (Bio)

    Bernard Laberge is a senior principal engineer in the video editors division at Avid. During his seven years with the company he has been actively involved in the replacement of the legacy video processing engines used by Avid editors with a common hardware-abstracted, component-based video processing engine currently running on the CPU with SIMD optimized code, GPU, and dedicated hardware.

    Abstract:
    Learn how to overcome the limitations of a thread-based scheduler, including dealing with the absence of recursive parallelism support and the inefficient handling of unbalanced processing load. Bernard Laberge addresses how Avid resolved the expensive refactoring of their thread-based scheduler into a task-based solution by choosing Intel® Threading Building Blocks (TBBs). He explores how Avid was able to easily integrate the Intel TBBs into their video editor applications and more than 5 million lines of code.

  • December 15, 2009
    How to Use Intel® Parallel Studio to Streamline Code Development in a Multicore Environment
    Speaker: Matt Dunbar, Director for Performance Technology, SIMULIA (Bio)

    Matt Dunbar is the director for performance technology at SIMULIA. Since joining the company in 1993, he has worked on parallelization of the Abaqus suite of products, initially for shared memory architectures and more recently for distributed memory architectures. Dunbar has also been intimately involved in selecting both the hardware and software tools used in the development of the Abaqus product line.

    Abstract:
    Resolve elusive, costly multithreading errors quickly and efficiently with Intel® Parallel Studio. While many coding problems that lead to bugs in software applications are typically straightforward logic errors, errors in managing memory and in multithreading code can sometimes take weeks to months to diagnose and fix. Matt Dunbar explores how and why taking advantage of multicore processors through multithreaded code is critical for compute-intensive applications. While spotlighting his work on SIMULIA's Abaqus finite element solver, Dunbar addresses the need for multicore execution and shares his experiences using Intel Parallel Studio to streamline code development in a multicore environment.