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NVIDIA Shaking Up the Parallel Programming World
An anonymous reader writes "NVIDIA's CUDA system, originally developed for their graphics cores, is finding migratory uses into other massively parallel computing applications. As a result, it might not be a CPU designer that ultimately winds up solving the massively parallel programming challenges, but rather a video card vendor. From the article: 'The concept of writing individual programs which run on multiple cores is called multi-threading. That basically means that more than one part of the program is running at the same time, but on different cores. While this might seem like a trivial thing, there are all kinds of issues which arise. Suppose you are writing a gaming engine and there must be coordination between the location of the characters in the 3D world, coupled to their movements, coupled to the audio. All of that has to be synchronized. What if the developer gives the character movement tasks its own thread, but it can only be rendered at 400 fps. And the developer gives the 3D world drawer its own thread, but it can only be rendered at 60 fps. There's a lot of waiting by the audio and character threads until everything catches up. That's called synchronization.'"
The articles sums up the hurdles of parallel programming and says that NVIDIA's CUDA is doing something to solve them but it doesn't say what. Even the short Wikipedia entry at http://en.wikipedia.org/wiki/CUDA tells more about it.
"News for Nerds, Stuff that matters".
But not if posted by The Ignorant.
What if the developer gives the character movement tasks its own thread, but it can only be rendered at 400 fps. And the developer gives the 3D world drawer its own thread, but it can only be rendered at 60 fps. There's a lot of waiting by the audio and character threads until everything catches up. That's called synchronization.
If a student of mine wrote this, a Fail will be the immediate consequence. How can 400 fps be 'only'? And why is threading bad, if the character movement is ready after 1/400 second? There is not 'a lot of waiting'; instead, there are a lot of cycles to calculate something else. and 'waiting' is not 'synchronisation'.
[The audio-rate of 7000 fps gave the author away; and I stopped reading. Audio does not come in fps.]
While we all agree on the problem of synchronisation in parallel programming, and maybe especially in the gaming world, we should not allow uninformed blurb on Slashdot.
From my experience, CUDA was much harder to take advantage of then multi-core programming. CUDA requires you to use a specific model of programming that can make it difficult to take advantage of the full hardware. The restricted caching scheme makes memory management a pain, and the global synchronization mechanism is very crude - there's a barrier after each kernel execution, and that's it. It took me a week to 'parallelize' port some simple code I had written to CUDA, whereas it took my an hour or so to add the OpenMP statements to my 'reference' CPU code. Sorry Nvidia - there is no silver bullet. By making some parts of parallel programming easy, you make others hard or impossible.
Nvidia unleashes Cuda attack on parallel-compute challenge