Additional GPU kernels added #62
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kmadhugit
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Aug 3, 2017
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kmadhugit
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Oct 23, 2017
* Spark 2.1 support * Sample codegen on top of DS * working sample * v2 * Stable jcuda codegen * Removed println * Removed the hardcoded size for partitions * code cleanup * Pinned Memory * Pinned Memory for GPUOUT * Array support * Array support 1 * Array Support * support for const array * made logical plan to produce & consume objects * incorporated review comments (#46) * incorporated review comments * include GpuDSArrayMult.scala sample file * GPU Caching Feature Added for GpuEnabler Dataset APIs (#49) * incorporated review comments * enable cache prelim * push cache setting to codegen part prelims * cached gpuPtrs handled in codegen part prelims * uncacheGPU for dataset included prelims * GPU dimensions support with provision for multiple stage execution prelims * handle constants - prelims * code package movement * handle constants - prelims2 * add comments - prelims2 * api's simplified * reorder gpuoutput in the args list * variable can be both GPUINPUT & GPUOUTPUT * variable can be both GPUINPUT & GPUOUTPUT bug fixes * started with testcase addition for GPU operations on Dataset * new testcases addition * cache bug fixes & new testcases added * bugs related to multithreading fixed * code comments added * code caching added for autogenerated code * cleaned up examples * cleaned up examples * Alloc host memory if the cached data is part of output * perf issue patched * minor mistake * include compare perf example * Performance & other misc patches (#50) * guava dependency wrong version fixed * prelim commit 1 * bug fixes * performance bug fixes * patch for perfDebug sample prog (#53) * API to load data into GPU (#56) * patch for perfDebug sample prog * Added loadGpu API * resolve conflicts * Added loadGpu API * resolve conflicts * samples invoke loadGpu * Performance optimization on speed and memory (#59) * auto caching added between GPU calls * toggle autocache gpu * logging added * testcase added for gpuonly cache * optimize mem alloc * reduce mem requirement * handle buffer underflow * optimize code flow * Support for Multi Dimension as input GPU Grid dimension (#60) * Additional GPU kernels added (#62) * auto caching added between GPU calls * toggle autocache gpu * logging added * testcase added for gpuonly cache * optimize mem alloc * reduce mem requirement * optimize code flow * sample program for logistic reg added * kmeans partial code drop * stabilize kmeans example * gpu memory limit check added * stabilize kmeans example * GpuKMeans example read from file * GpuKMeans example dump cluster index * minor patches * introduce gpuptr meta info & bug fixes * child gpuptrs cleanup bug fixed * GpuKMeans variants added * optimize loadGpu * optimize loadGpu * optimize loadGpu * optimize loadGpu * modify perfDebug to remove sleep * code cleanup * remove duplicate testcase * #Issue63: Support for CUDA8.0 and related jcuda libraries (#64) * changes for jcuda 8.0 * Address performance issue in map GPU functions (#67) * Heterogeneous Environment Support (#69) * Heterogeneous Environment Support * changes for Heterogeneous env and null dataset assertion * GPUEnabler version changed to 2.0.0 * GPUEnabler version changed to 2.0.0 * Update README.md
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This PR includes the following enhancements:
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