Tutorial slides (PDF) - Clemson University
Tutorial slides (PDF) - Clemson University
Tutorial slides (PDF) - Clemson University
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
NumPy - FLOPS<br />
Optimized BLAS available via NumPy via np.dot. Handles<br />
general inner product of multi-dimensional arrays.<br />
Very difficult to cross-compile on BG/P. Blame disutils!<br />
core/_dotblas.so is a sign of optimized NumPy dot<br />
Python wrapper overhead is negligible<br />
For matrix * vector products, NumPy dot can yield better<br />
performance than direct call to GEMV!<br />
Fused floating-point multiply-add instructions are not<br />
created for AXPY type operation in pure Python. Not<br />
available in NumPy either.<br />
for i in xrange(N):<br />
Y[i] += alpha*X[i]<br />
C[i] += A[i]*B[i]
Change language