Speed Up Small-Matrix Multiplication - Intel® Math Kernel
- Project length: 0h 57m
A major focus of Intel® Math Kernel Library—one of five free Intel® Performance Libraries—is to dramatically improve small-matrix multiplication run-time performance in compute-intense applications such as those used in applied mathematics, physics and engineering.
In this webinar we’ll look at new Intel® MKL capabilities, compare and contrast them for different matrix multiplication uses cases, and show you code samples and benchmark results for different sizes of problems.
Presenter: Murat Guney
Murat E. Guney received his B.S./M.S. degrees from Middle East Technical University, and M.S./Ph.D. degrees from Georgia Institute of Technology. His main interests are high-performance/parallel computing, performance optimizations, sparse solvers, and numerical methods. He is currently a Software Engineer for the Intel Math Kernel Library.