Did You Just Call me a 'Programmer'?
You can get five programmers in a room to give you six different definitions of parallelism. I've been in situations where a bunch of programmers were throwing the terms "parallel programming" and "multithreading" around assuming that they were all on the same page. I have to be careful because these days even the term "programmer" carries a certain amount of controversy, depending on the company one keeps.
I guess we would still get the multi-definition result for parallelism if we were talking about five "software developers" as well. I reckon I really mean those folks who actually write the code whether we call them developers or programmers.
There is a tendency to forget that not every one does the same kind of software development that you do. So when we talk about the problems of parallel programming and the impending paradigm shift required to take advantage of massive multicore, we have to discriminate between the levels and layers of parallel programming. If I'm writing a device driver for a multicore graphics chip, that's a very different kind of parallel programming than if trying to deal with a multi-user ATM banking application. The real-time concurrency requirements of the multi-user banking application is a far cry from what the developers are facing when dealing with multi-user, multi-transaction, web containers. Depending on where you're at in the software development jungle you may see the parallel programming/multicore dilemma very differently than someone else located in a different jungle space. Tracey and I are guilty of trying to characterize our intersection with parallel programming as the domain level problem solving variety. It can seem murky if you're not quite clear what we mean.
Figure 1 is one (we have others) rough overview of the layers of parallel programming that we've encountered on our trek toward the ultimate concurrency. The person doing work at Level 5 in Figure 1 sees the multicore issue very differently than the person doing work at Level 3. When we talk about a dramatic paradigm shift being necessary in order to truly navigate massive multicore, we have to be context specific. Do we mean a paradigm shift at the hardware level, instruction level, operating system level, etc.? If you follow this multithreading stuff closely there has been advancements at various levels. But at which level in Figure 1 are we all referring to when we suggest a dramatic change in thinking is needed?
Our goal of getting the computer to truly answer the question:
Which tastes better coke or pepsi?
requires massive parallelism at Level 1. Without massive parallelism at Level 1, the computer doesn't stand a chance of answering our question, if indeed it can answer the question at all. The problem is that at Level 1 most programmers (whoops, I mean "developers") have been indoctrinated to think and solve problems in a linear and sequential fashion. Our notions of space and time are based on the story-telling-model where everything has a beginning, middle, and end. Especially our computer algorithms. And herein lies the rub.
Tracey and I are applying lessons learned from the ghosts of ICOT to what we believe is a paradigm shift for Level 1. A story that prefers a recursive spiral to the notion of beginning and inductive rings to the notion of ending and complete abandonment to the once-upon-a-time-model. Complexity, problem solving, search, path finding, reasoning, and massive multicore all have a rendevous with destiny at Level 1. Level 1 is where Tracey and I plan to catch the notorious and evasive snipe.
This Week's Multicore Reading List
MATLAB and Google App Engine
Logging In C++ : Part 2
Improving log granularityA Conversation with BitMagic's Developer
Prefer Structured Lifetimes: Local, Nested, Bounded, Deterministic
- Intel Parallel Studio; Download the free eval today!
- Parallelism Breakthrough Video Series; Watch and learn more about Intel® Parallel Studio
- 2009 Intel Software Webinar Series; View On-Demand webinars
- Coding for Multi-core Processes; Intel® Compiler Pro eBook
- Performance Through Parallelism; Intel® Tuning for Vista eBook
- Intel® Software Network; Connect with developers and Intel engineers
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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.



