Title: Portable Compilation of Sparse Computation
Abstract:
Hardware is becoming more diverse and architects are designing a host of new accelerators. Different types of accelerators are being deployed in different data centers, making it harder to port applications across machines and across clouds. I will discuss the design of compilers for data-intensive application in heterogeneous systems. I will then describe how to compile sparse tensor algebra and array operations to the major classes of heterogeneous hardware: CPUs, fixed-function accelerators, GPUs, distributed machines, and streaming dataflow accelerators. Finally, I will discuss the promise of portable compilation of more general classes of computations.
Bio:
Fredrik Kjolstad is an Assistant Professor in Computer Science at Stanford University. He works on topics in compilers, programming models, architecture, and systems, with an emphasis on fast compilation and compilers for sparse computing problems where we should separate the algorithms from data representation. He has received the MIT EECS Sprowls PhD Thesis Award, the NSF CAREER Award, a Google Research Scholarship, and three distinguished paper awards.