Back to Bits: Extending Shannon’s communication performance framework to computing

This presentation proposes a novel measurement unit for computing performance grounded in information theory. Modern computing systems are increasingly diverse, supporting low-precision formats, hardware specialization, and emerging paradigms such as analog, quantum, and reversible logic. Traditional metrics like floating-point operation (flop) counts no longer accurately capture this complexity. Instead, I frame computing as the transformation of information through a channel and define performance in terms of the mutual information between a system’s inputs and outputs. This approach measures not just the quantity of data processed, but the amount of meaningful information encoded, manipulated, and retained through computation. The framework provides a principled, implementation-agnostic foundation for evaluating performance.