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On The Connection Machine: "Beautiful thesis, though it doesn't tell you anything you can really do today." I don't understand: is data-parallel computing on a
by abecedarius 12y ago
On The Connection Machine: "Beautiful thesis, though it doesn't tell you anything you can really do today."
I don't understand: is data-parallel computing on a GPU much worse somehow? Or is it that there are better sources to read about data-parallel algorithms?
- prestonbriggs 12y agoYeah, data-parallel computing on a GPU doesn't really approach what Hillis was aiming for. Check especially CM Lisp; great stuff.
- sedachv 12y ago> is data-parallel computing on a GPU much worse somehow? OpenCL is a very awkward way to do vector processing - everything is hard-coded to an abstract model of a typical consumer GPU memory hierarchy. CUDA is even worse with a ton of versions all having different limitations according to what the Nvidia chips can do. It's awkward to do a lot of SIMD tasks on GPUs. The Connection Machine was a general-purpose SIMD originally designed for parallel graph algorithms. OpenCL looks like what the Connection Machine C* language might get macroexpanded into prior to compilation: http://people.csail.mit.edu/bradley/cm5docs/CStarProgrammingGuide.pdf http://people.csail.mit.edu/bradley/cm5docs/CStarProgramming...
- abecedarius 12y agoThanks. I've read Hillis's book but not studied the modern stuff; I'd gotten the impression the hardware was capable of about as much, and faster now, even if organized differently -- shared memory instead of a network -- and with less-pleasant languages.
- sedachv 12y agoThat was pretty much where Thinking Machines was headed before bankruptcy - their third model (CM5) was a SPARC cluster primarily for running Connection Machine Fortran and C*.