Titel: KIK-Vortrag "Large-scale FPGA implementations of M..
Startdatum: 05 Juli
Startzeit: 16:00
Stoppzeit: 17:00Uhr
Veranstalter: FG Intelligente Eingebettete Systeme
Ort: Wilhelmshöher Allee 71-73, Hörsaal 0315

Prof. Philip Heng Wai Leong
(University of Sydney)

FPGA implementations of machine learning algorithms have been shown to be extremely efficient when the problem fits entirely on the FPGA but it remains a challenge to scale to problems of interest to industry. In this talk, our recent research on how to increase the capacity of existing approaches will be described.


In the first part of the talk we will describe an implementation of the Fastfood algorithm for scaling up online kernel methods. By utilizing the theory of random projections, problems with 1000x larger input dimension and dictionary size can be solved. A systolic implementation that operates at 500 MHz clock frequency was achieved. The second part of the talk describes an open-source matrix multiplication library for the Xeon+FPGA platform. This supports a number of different precisions down to binary, and additional support for deep learning applications is provided. Performance approaching the maximum of 14 Xeon cores and an Arria 10 FPGA was achieved.