Hi Karli,
I went through the paper you sent me that talks about sub-vectors and
sub-matrices for the Householder reflections by the use of what you call
proxy objects.
I had some questions that stem from reading that paper.
1. About the back-end: The paper talks about OpenCL as the back-end. As I
understand OpenCL uses a Just-in-Time compiler, for an equivalent OpenCL
kernel to be generated on the fly for each high-level expression with a
ViennaCL type. What about the case of CUDA which uses the nvcc compiler
more like the g++ compiler, how does that get translated for expressions
containing ViennaCL types?
2. I am assuming the use of temporary variables and swapping between the
CPU and GPU should be minimized during development for memory and speed
reasons. Also one should probably be careful to understand how often the
JIT OpenCL kernel generation is launched.
3. I did also read the Halko-Tropp(http://arxiv.org/pdf/0909.4061.pdf) SVD
paper on the Rank-k SVD approximations using a random projection. Their
chief argument is that their algorithm for rank-k SVD approximation of an m
by n matrix is O(mn*log(k)) compared to the usual O(mnk). I am assuming
that is the reason you pointed me to that work. I still am to run profiling
on the current SVD implementation, which I guess could be slow for a number
of reasons, including the anything in the code that might cause a PCI-e
transfer.
Any clarifications you could provide would help. I'll post a few other
questions in due course of time.
Regards,
Aanchan
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