Algo-Logic Systems Demonstrates Scale-Out Machine Learning and Real-time Inference Accelerated by FPGA Key-Value Store at SC17

San Jose, California, November 9, 2017 – Algo-Logic Systems will demonstrate machine learning and real-time inference accelerated by their Key Value Store (KVS) running on a Field Programmable Gate Array (FPGA) at the Super Computing 2017 conference. The application to train and control self-driving cars will be demonstrated at the upcoming conference on November 13th through the 16th, 2017 in Denver, Colorado. In the demonstration, parallel simulations of cars are run and data is shared between computation nodes using Algo-Logic’s networked-attached KVS. Simulated sensor input and data from the KVS are used to control real-time inputs to self-driving cars.

The demonstration highlights the capabilities of Algo-Logic’s hardware accelerated, in-memory KVS scale-out to support data center applications. Parallel simulations of a Markov model are run and data is shared between computation nodes using Algo-Logic’s networked-attached KVS that runs entirely in FPGA logic and interfaces through a software API to standard computation servers.