In our coverage of the semiconductor space, we typically think of two main vectors of hardware – the CPU and the GPU. Beyond that, we look at FPGAs, microcontrollers, and this decade is bringing the advent of the dedicated AI processor. What ties all of these products together is actually the FPGA – a field programmable gate array that allows a skilled technician to essentially build a custom circuit out of configurable gates. This means an FPGA can be used to design and simulate a full CPU or GPU, but also an FPGA offers a reconfigurable way to offer optimized compute power that adapts to the needs of its users without the cost of millions or tens of millions to design dedicated silicon. One of the first FPGA companies on the market was Lattice Semiconductor, which now focuses on small power efficient FPGA designs that end up in everything from consumer devices to servers.
Over the last three years at Lattice, Jim has initiated a cultural shift that is playing out in the company roadmaps – new products, a more agile approach, and a need to focus on enabling machine learning at every part of its product stack. The recent financial disclosures at Lattice show an increasing demand for its hardware, as well as the company making strides to double its addressable market over the next five years. I thought this would be a good time to reconnect with Jim to find out exactly what he’s doing at Lattice to earmark the next generation of growth at this foundational FPGA company.