Very good video, it contains answers to many of the questions that people are speculating here about and other interesting things about Tesla's custom chip. -

Very good video, it contains answers to many of the questions that people are speculating here about and other interesting things about Tesla's custom chip. - It's under 100W so they can retrofit into old cars - lower part cost, so they can do full redundancy with doubling the parts - they estimated that 50 TOPS is needed for self-driving - lower latency with batch size of 1 compared to TPU's 256 + GPU for post-processing - security: only code signed by Tesla can run on the chip - at the time (2016) there was no neural net accelerator chips - some part's are built from bought IP (so not reinventing them) Probably things like the 12 ARM CPUs, LP DDR4 memory, video encoder, maybe the separate post-processing GPU too... - physical size of the board is small - performance example: on CPU 1.5 FPS, on GPU (600 gflop) 17 FPS, on Tesla's NN accelerator 2100 FPS - Besides the convolution even the ReLU and Pooling is implemented in hardware - Paying attention to the energy efficiency down to the arithmetic and data type usage. - The silicon cost is less than their previous hardware (HW 2.5) - old hardware 110 FPS new one 2300 FPS - 144 TOPS compared to NVidia's Drive Xavier 21 TOPS