Analytically Modeling Application Execution for Software-Hardware Co-design

Abstract

Software-hardware co-design has become increasingly important as the scale and complexity of both are reaching an unprecedented level. To predict and understand application behavior on emerging or conceptual systems, existing research has mostly relied on cycle-accurate micro-architecture simulators, which are known to be time-consuming and are oblivious to workloads' control flow structure. As a result, simulations are often limited to small kernels, and the first step in the co-design process is often to extract important kernels, construct mini-applications, and identify potential hardware limitations. This requires a high level understanding about the full applications' potential behavior on a future system, e.g. the most time-consuming regions, the performance bottlenecks for these regions, etc. Unfortunately, such application knowledge gained from one system may not hold true on a future system. One solution is to instrument the full application with timers and simulate it with a reasonable input size, which can be a daunting task in itself. We propose an alternative approach to gain first-order insights into hardware-dependent application behavior by trading off the accuracy of analysis for improved efficiency. By modeling the execution flows of user applications and analyzing it using target hardware's performance models, our technique requires no cycle-accurate simulation on a prospective system. In fact, our technique's analysis time does not increase with the input data size.