I am really new to programming and Cuda. Basically I have a C function that reads a list of data and then checks each item against a hashmap (I'm using uthash for this in C). It works well but I want to run this process in Cuda (once it gets the value for the hash key then it does a lot of processing), but I'm unsure the best way to create a read only hash function that's as quick as possible in Cuda.
Basically I'm trying to value a very very large batch of portfolio as quickly as possible. I get several million portfolio constantly that are in the form of two lists. One has the stock name and the other has the weight. I then use the stock name to look up a hashtable to get other data(value, % change,etc..) and then process it based on the weight. On a CPU in plain C it takes about 8 minutes so I am interesting in trying it on a GPU.
I have read and done the examples in cuda by example
so I believe I know how to do most of this except the hash function(there is one in the appendix but it seems focused on adding to it while I only really want it as a reference since it'll never change. I might be rough around the edges in cuda for example
so maybe there is something I'm missing that is helpful for me in this situation, like using textual or some special form of memory for this). How would I structure this for best results should each block have its own access to the hashmap or should each thread or is one good enough for the entire GPU?
Sorry just to clarify, I'm only using C. Worst case I'm willing to use another language but ideally I'd like something that I can just natively put on the GPU once and have all future threads read to it since to process my data I'll need to do it in several large batches).
There is a hash_map extension for CUDA Thrust, in the cuda-thrust-extensions library. I have not tried it.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With