Can it be parallelized? That is how you reduce run-time. One of the tests
matrix-matrix multiplication has been successfully speeded up by using GPUs.
CUDA is the language used for this, which is a derivative of C. To be fair you
only see the benefit for really large matrices, smaller ones which actually be
slower on GPUs.
In answer to your question, YES!
Adam
Scientific computing’s future: Can any coding language top a 1950s
behemoth?
Cutting-edge research still universally involves Fortran; a trio of
challengers wants in.
---
Includes a JPEG image of a Hollerith card for the younguns who have
never seen one.
"Julia may be the first language since Fortran created specifically with
scientific number crunching in mind."
"Fortran has been consistently regarded as the fastest language available
for numerical work, and it remains the standard used for comparatively
benchmarking supercomputers. But what does it mean for a language to be
fast?"
"Julia’s published benchmarks show it performing close to or slightly
worse than C, and Fortran, as usual, performing better than C for most
tasks."
http://julialang.org/benchmarks/
"The epigraph that opens this article notwithstanding, there is a
reasonable chance that the language of choice for scientific computing in
another decade will be called “Julia.”"
Discuss.
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Things Serve the Beam
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David J. Schuller modern
man in a post-modern world MacCHESS, Cornell
University [email protected]