The Price of Performance

In the late 1990s, our research group at DEC was one of a growing number of teams advocating the CMP (chip multiprocessor) as an alternative to highly complex single-threaded CPUs. We were designing the Piranha system,1 which was a radical point in the CMP design space in that we used very simple cores (similar to the early RISC designs of the late ’80s) to provide a higher level of thread-level parallelism. Our main goal was to achieve the best commercial workload performance for a given silicon budget. Today, in developing Google’s computing infrastructure, our focus is broader than performance alone. The merits of a particular architecture are measured by answering the following question: Are you able to afford the computational capacity you need? The high-computational demands that are inherent in most of Google’s services have led us to develop a deep understanding of the overall cost of computing, and continually to look for hardware/software designs that optimize performance per unit of cost.