Tyler’s research interests are in developing and understanding models for testing and safely developing GPU applications which contain irregular computations. In particular, he examines issues related to the GPU relaxed memory model and execution model. He received his MSc from University of Utah in 2014 and worked as an intern for the Nvidia compiler team during the summers of 2013 and 2014.
His personal page is here.
Forward Progress on GPU Concurrency
28th International Conference on Concurrency Theory (CONCUR'17)
Cooperative Kernels: GPU Multitasking for Blocking Algorithms
11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE'17)
Portable Inter-workgroup Barrier Synchronisation for GPUs
31st Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA'16)
Exposing Errors Related to Weak Memory in GPU Applications
37th Annual ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI'16)
The Hitchhiker's Guide to Cross-Platform OpenCL Application Development
4th International Workshop on OpenCL (IWOCL'16)
GPU Concurrency: Weak Behaviours and Programming Assumptions
20th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'15)