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CUDA documentation: * [[http://www.nvidia.co.uk/object/cuda_develop_emeai.html|NVIDA website]] CUDA issues: * Memory bandwidth limits algorithms - matrices n**2 entries to get in and out, matrix multiplication O(n**2.7), but for integers n limbs to get in and out O(n log n log log n) operations to multiply Other Options: * AMD Math library AML provides BLAS interface uses GPU - but that's for linear algebra * PTX NVIDIA GPU assembler code for inner loops Gonzalo Tornaria (theta functions expert) * Is there a way to encode integer multiplication in linear algebra? (A. Perhaps vectors - multimodular, but not matrices) * Kernel * Launch threads - issues based on hierarchy of memory - CPU registers-> memory per processor block-> main graphics memory-> system memory * Can launch all the threads on all cpus in a couple of cycles |
MPIR - Parallel Algorithms and CUDA
Present : Carl Witty, Bill Hart, Michael Abshoff, Glenn Tarbox Virtually Present : Jeff Gilchrist, Gonzalo Tornaria
You can chat in a Linux text console by installing "irssi" and running: "irssi -c irc.freenode.net" and then type "/join #sage-devel"
Parallel algorithms:
- Multimodular algorithms
- Scalar algorithms
Peter Montgomery's remainder algorithm a mod b, precompute b1 = B mod b, b2 = B2 mod b, b3 = B3 mod b, then write a = a0 + a1*B + a2*B^2 +..., then compute a0 + a1*b1 + a2*b2 +.... and do final reduction mod b. Multiplications can be done in parallel.
- Addition and subtraction can be parallelised using nails - non-unique representation of numbers
- Classical algorithm is embarrassingly parallel - bad if you have an n log n algorithm in that range
Glenn Tarbox (Owner of cuda1, AMD K10 with NVIDA CUDA card - expert on large scale parallelisation)
- What are the top level integration issues, e.g. by libraries using MPIR
Michael Abshoff (Sage release manager)
- Link into Sage via cython and link in CUDA
CUDA documentation:
CUDA issues:
- Memory bandwidth limits algorithms - matrices n**2 entries to get in and out, matrix multiplication O(n**2.7), but for integers n limbs to get in and out O(n log n log log n) operations to multiply
Other Options:
- AMD Math library AML provides BLAS interface uses GPU - but that's for linear algebra
- PTX NVIDIA GPU assembler code for inner loops
Gonzalo Tornaria (theta functions expert)
- Is there a way to encode integer multiplication in linear algebra? (A. Perhaps vectors - multimodular, but not matrices)
- Kernel
Launch threads - issues based on hierarchy of memory - CPU registers-> memory per processor block-> main graphics memory-> system memory
- Can launch all the threads on all cpus in a couple of cycles