BEYONDMOORE addresses the timely research challenge of solving the software side of the Post Moore crisis. The techno-economical model in computing, known as the Moore’s Law, has led to an exceptionally productive era for humanity and numerous scientific discoveries over the past 50+ years. However, due to the fundamental limits in chip manufacturing we are about to mark the end of Moore’s Law and enter a new era of computing where continued performance improvement will likely emerge from extreme heterogeneity. The new systems are expected to bring a diverse set of hardware accelerators and memory technologies. Current solutions to program such systems are host-centric, where the host processor orchestrates the entire execution. This poses major scalability issues and severely limits the types of parallelism that can be exploited. Unless there is a fundamental change in our approach to heterogeneous parallel programming, we risk substantially underutilizing upcoming systems. BEYONDMOORE offers a way out of this programming crisis and proposes an autonomous execution model that is more scalable, flexible, and accelerator-centric by design. In this model, accelerators have autonomy; they compute, collaborate, and communicate with each other without the involvement of the host. The execution model is powered with a rich set of programming abstractions that enable a program to be modeled as a task graph. To efficiently execute this task graph, BEYONDMOORE will develop a software framework that performs static and dynamic optimizations, issues accelerator-initiated data transfers, and reasons about parallel execution strategies that exploit both processor and memory heterogeneity. To aid the optimizations, a comprehensive cost model that characterizes both target applications and emerging architectures will be devised. Complete success of BEYONDMOORE will enable continued progress in computing which in turn will power science and technology in the life after Moore’s Law.
Funding SchemeERC-STG - Starting Grant
See on map