Banu Nagasundaram offers an overview of Intel’s Deep Learning Boost (Intel DL Boost) technology, featuring integer vector neural network instructions targeting future Intel Xeon scalable processors. These instructions improve throughput of multiply-add operations with int8 and int16 data types and are used to achieve performance gains in low-precision convolution and matrix-matrix multiplication operations used in deep neural networks. Banu walks you through the 8-bit integer convolution implementation made in the Intel MKL-DNN library to demonstrate how this new instruction is used in optimized code.
Banu Nagasundaram is a product marketing manager with the Artificial Intelligence Products Group at Intel, where she drives overall Intel AI products positioning and AI benchmarking strategy and acts as the technical marketer for AI products including Intel Xeon and Intel Nervana Neural Network Processors. Previously, Banu was a product marketing engineer with the Data Center Group at Intel, where she supported performance marketing for Xeon Phi, Intel FPGA, and Xeon for AI; was a design engineer on the exascale supercomputing research team with Intel Federal; and worked at Qualcomm doing design verification of mobile processors. Banu holds an MS in electrical and computer engineering from the University of Florida and is working toward an MBA at UC Berkeley’s Haas School of Business.
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