PROJECT2: SOMANSHU AGARWAL #6
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The project was divided into two sub projects:
Stream Compaction: The motive in the project was to analyze the Naive, Work-Efficient and Thrust implementations in GPU and compare the run time with serialized CPU and make the analysis. I analyzed the performance with varying block size and input array and made inferences on the bottlenecks of the algorithms and reasoning behind it.
Character Recognition: The motive was to train a Neural Network that would train on the given data set and recognize the alphabets of the given classes. We first train and check the Neural network on XOR inputs and output and then check on the character recognition. The weights of the arrays, soft max probabilities and the hidden layer unit values are provided in the .txt files. Also, loss vs iterations plots are given for analysis.