Engineering Commons^™

Power-Efficient And Highly Scalable Parallel Graph Sampling Using Fpgas, Muhammad Usman Tariq

Masters Theses

Energy efficiency is a crucial problem in data centers where big data is generally represented by directed or undirected graphs. Analysis of this big data graph is challenging due to volume and velocity of the data as well as irregular memory access patterns. Graph sampling is one of the most effective ways to reduce the size of graph while maintaining crucial characteristics. This thesis presents design and implementation of a field programmable gate array (FPGA) based graph sampling method which is both time- and energy-efficient. This is in contrast to existing parallel approaches which include memory-distributed clusters, multicore and GPUs. …