Progress toward full vehicle autonomy depends on the ability to real-time process large volumes of sensor information. With Elon Musk’s comments on the future of LiDAR at Tesla’s Autonomy Investor Day in April, the AV (autonomous vehicle) implementation and economics debate continues to be a popular topic.
Whether the sensor fusion is camera- or LiDAR-driven, we expect the compute load to remain roughly similar. Considering a self-driving car generates four terabytes of stored data in about an hour and a half—a number that will grow as capabilities evolve—manufacturers need to rely on sensor fusion infrastructure that is not only powerful and versatile, but also hardened to withstand real-life road conditions. Most of our customers have settled on 48-56 Intel Xeon cores and approximately 360 TFLOPS (trillion floating-point operations per second) of tensor-core capability within an AV system.