Matrix Multiplications on Apache Spark through GPUs

Sammanfattning: In this report, we consider the distribution of large scale matrix multiplications across a group of systems through Apache Spark, where each individual system utilizes Graphical Processor Units (GPUs) in order to perform the matrix multiplication. The purpose of this thesis is to research whether the GPU's advantage in performing parallel work can be applied to a distributed environment, and whether it scales noticeably better than a CPU implementation in a distributed environment. This question was resolved by benchmarking the different implementations at their peak. Based on these benchmarks, it was concluded that GPUs indeed do perform better as long as single precision support is available in the distributed environment. When single precision operations are not supported, GPUs perform much worse due to the low double precision performance of most GPU devices.