Cuda Jobs

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Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
Task: With a MxN matrix, get every X combination of columns, then run analysis. For example if I want combos of X=2, it would be col1+col2, col1+col3, col2+col3, etc. So for each col grouping, I slice from the matrix (keeping those cols of interest) and run conditional analysis. The analysis is basically: when col1 is in the 1st quartile and col2 is in the 3rd quartile, what is the result. The MxN matrix is relatively small in terms of KB’s but with many columns and col-combos of 3 or 4, there are many, many permutations of the subsets. And cumulatively the subsets add up to become large files (tens of GBs). So the use-case is a lot of slicing, then performing a rank of the subsets then aggregating. Please provide a high level implementation plan. Then if it sounds reasonable, I will reply with a sample python script that should be moved to the GPU. Only GPU experts respond please.
Skills: CUDA OpenCL Python
Fixed Price Budget - Expert ($$$) - $500 to $1,500 - Posted
Looking for an expert who can quickly provide an application in CUDA /OpenGL for Windows 7. You can choose the version of CUDA / OpenGL. Application must demonstrate CUDA processed data displayed directly to video output buffers of multiple GPU outputs. ... Application must demonstrate CUDA processed data displayed directly to video output buffers of multiple GPU outputs. ... Application must demonstrate CUDA processed data displayed directly to video output buffers of multiple GPU outputs. If you are a CUDA and OpenGL expert, I want to hear from you, please contact and I will provide detailed project specification.
Skills: CUDA OpenGL
Fixed-Price - Intermediate ($$) - Est. Budget: $300 - Posted
Looking for an experienced developer who can take a C++ function (objective function in a non-linear optimizer) which has matrix/vector operations on a dataseries, and port to GPU cores, to run many functions in parallel. You need to develop a host test application, which loads many objective functions inside GPU cores, host sends the "shared" as well as local data to these functions and runs them in parallel, brings the data back to the host and print results in a file. This is a sub project of a large project. We are trying to port DEOptim non-linear optimizer from R in C++ using host GPU configurations. This objective function is the objective function of DEOptim for stock portfolio optimization. You can google and see the project in R.
Skills: CUDA