Extracting INT8 Multipliers from INT18 Multipliers

With the advent of machine learning as perhaps the most high-profile application area for FPGAs, there is a compelling reason to improve the provision of smaller precision arithmetic on these devices. INT8 is commonly used for AI inferencing, and along with some additional soft logic for exponent handling, can be an effective solution for training as well. This paper describes techniques for efficiently extracting INT8 multipliers from commonly available INT18 multipliers found in many modern FPGAs. A small amount of soft logic - as little as 7 ALMs per INT8 multiplier - is required to provide pre or post multiplier correction to calculate two INT8 multiplies from a single 18x18 multiplier. We present two configurations for both signed and unsigned representations where two multiplications share one input operand. In addition to the individual INT8 variants, we present full device cases of 22,400 INT8 multipliers organized as DOT32 product arrays, with the soft logic tightly bound to the INT18 based DSP Blocks. A majority of the soft logic and routing in the device is left untouched, and available for application development.