Accomplishments
Theodor has been calculating timings for our FPU operations.
There are a couple of things to point out here:
- There are cycle counts for the assignment time. This is the number of cycles between the time that the pkt_avail signal is asserted to the Data Pipeline Router and the time that the dpr_done signal is asserted. This is the time it takes to assign a model to a model manager once the packet is on the board
- Single-Model train cycle. This is the amount of cycles to run one forward/backward/update pass on a single input for the given model, assuming that only one model is training on the board.
- Double- and Quadruple-Model train cycles. This is the amount of cycles to run one forward/backward/update pass on a single input for two or four models are training simultaneously on the board. These columns are empty because Theodor is still filling them out and making small corrections and optimizations to the implementation.
Jared has been supporting integration with the host machine and the data pipeline router. The memory interface in the hardware supports the common memory protocol and the Pi hosts servers to communicate with the host.
Schedule and Accomplishments for Next Week
In preparation for the final report, Theodor will be filling out the above table and getting numbers for various numbers of models being trained simultaneously on one board. Our model throughput for the single-model implementation was not impressive, so we will try training some of our smaller models (of which there are more, now that we aren’t running convolutional layers) on M9k memory, which has single-cycle dual-port read.
Jared will be finalizing integration for more accurate metrics and to possibly meet our integration goal.
Mark will be helping Jared with integration as well as finalizing some GPU benchmarks and working on the final report.