Hello Tomas, > Could you please elaborate more why to choose CUDA, a nvidia-only > technology, rather than OpenCL, supported by much wider range of > companies and projects? Why do you consider OpenCL unsuitable? > > Not that CUDA is bad - it certainly works better in some scenarios, but > this is a cost/benefits question, and it only works with devices > manufactured by a single company. That significantly limits the > usefulness of the work, IMHO.
I will never say OpenCL is unsuitable, I just meant, as per the research I did, CUDA came out with better results. I do agree OpenCL is also a great tool to exploit the power of GPUs. My aim is to enhance the performance using CUDA, though OpenCL implementation might work great too! > You mention that you ran into issues with PG Strom. What issues? While I was trying to compile, I ran into the error "src/main.c:27:29: fatal error: utils/ruleutils.h: No such file or directory", when I did make to the branch of Postgres suggested in the description, i.e the custom_join branch, I still ran into the same issue. Moreover, I couldn't locate the file. > Can we see some examples, what this actually means? What you can and > can't do at this point, etc.? Can you share some numbers how this > improves the performance? I did some benchmarking on quicksort for 1M random numbers(range 0 to 0xffffff) on GPU and CPU, the results showed enhancement of 700% on the GPU. What this means and what I can do at this point - My aim was to integrate CUDA with Postgres so that I can make a call to the GPU for sorting operation. To start, I made a simple CUDA hello world program, and edited the code to call it from qsort, ran into name mangling issues, so sorted that out by creating 2 different .h files one for CUDA program and for the call I made from qsort. Finally, edited the make file to compile the CUDA program with the Postgres compilation itself and now when I compile my Postgres code, the CUDA file gets compiled too and prints the needed on the server end. What I still haven't done - I still haven't actually enhanced the sorting yet, I'm still analyzing the code, how to tinkle with it, the right approach. > That's really difficult to judge, because you have not provided any > source code, examples or anything else to support this. > > > > > Please give in your valuable suggestions and views on this. > > From where I sit, this looks interesting, but rather as a research > project rather than something than can be integrated into PostgreSQL in > a foreseeable future. Not sure that's what GSoC is intended for. > > Also, we badly need more details on this - current status, examples, and > especially project plan explaining the scope. It's impossible to say > whether the sort can be implemented within the GSoC time frame. What I actually see it is as is to be a branch of Postgres which has CUDA compatible features. I wanted to start it by sorting which can further be improved. To be honest, I'm still analyzing the sort code for elements above a million integer elements(in a single row, for now) so that the use of GPUs is actually significant. As I saw, Postgres uses external sort for that. If you feel this isn't feasible in such a time span, I would love to hear any suggestion for any small function which can leverage off by parallelism. Thanks and Regards,Hitesh Ramani
