Sort by
Refine Your Search
-
hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
-
-level code and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware
-
Description Dr. Kinga Makovi at the Center for Interacting Urban Networks (CITIES), New York University Abu Dhabi, seeks to recruit a computational social science Postdoctoral Researcher to support
Enter an email to receive alerts for distributed-computing-"Multiple" positions