Wang is developing a new execution model for dynamic parallelism found in unstructured applications with irregular data structures such as relational queries and graph analysis. The goal is to pursue both the compiler and micro-architectural support of this model to discover and exploit dynamically formed pockets of structured data parallelism in irregular applications that can use GPU compute and memory bandwidth.

Wang works in the Computer Architecture and Systems Laboratory (CASL), which is led by ECE Professor Sudhakar Yalamanchili. Wang is Yalamanchili’s second student to receive an NVIDIA Graduate Fellowship. Fellow CASL Ph.D. student Haicheng Wu was selected this honor in both 2011-12 and 2012-13. 

The NVIDIA Graduate Fellowship Program is open to applicants worldwide. Eligibility criteria include completion of the first year of Ph.D. level studies in the areas of computer science, computer engineering, system architecture, electrical engineering or a related area. To learn more about the program, visit http://blogs.nvidia.com/blog/2014/04/17/acing-gpu-u/#sthash.MKVsu1vW.dpuf.