pengyu965 / cse570-parallel-distributed-processing

Implementation of Parallel and Distributed Processing assignments

CSE 570 : Introduction to Parallel and Distributed Processing

Requirements

• A CCR node from the GPGPU-capable partition with CUDA 8.0 will be used for testing.
• Your code will be tested for efficiency.

Assignment 1:

• Implement an efficient NVIDIA CUDA program for Gaussian kernel density estimate.
• Assumptions
  • The input vector X and output vector Y are single precision.
  • The size n of vectors X and Y exceeds capacity of a single CUDA thread block, but is small enough to be processed by a single kernel invocation.

Assignment 2:

• Implement efficient end-to-end Apache Spark program for finding connected components in an undirected graph
• Assumptions
  • The undirected graph G is too large to fit into a single compute node.
  • The graph G is represented by a list of edges in the form of source target where source is the source vertex id and target is the target vertex id. The vertices are represented as integers. Assume the graph has no self loops. The list of edges are provided as a text file.