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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Atlanta, GA | Posted: April 29, 2014
Jackie Nemeth
School of Electrical and Computer Engineering
404-894-2906
Summary Sentence:
ECE Ph.D. student Jin Wang has been chosen for the prestigious NVIDIA Graduate Fellowship.
Full Summary:
ECE Ph.D. student Jin Wang has been chosen for the prestigious NVIDIA Graduate Fellowship.
Jin WangJin Wang, a Ph.D. student in the Georgia Tech School of Electrical and Computer Engineering (ECE), has been selected for the prestigious NVIDIA Graduate Fellowship. Wang was among five Ph.D. students chosen for this award from an international field of more than 100 applicants from 21 countries.
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.
