Emergent Mind

Abstract

Programmability, performance portability, and resource efficiency have emerged as critical challenges in harnessing complex and diverse architectures today to obtain high performance and energy efficiency. While there is abundant research, and thus significant improvements, at different levels of the stack that address these very challenges, in this thesis, we observe that we are fundamentally limited by the interfaces and abstractions between the application and the underlying system/hardware--specifically, the hardware-software interface. The existing narrow interfaces pose two critical challenges. First, significant effort and expertise are required to write high-performance code to harness the full potential of today's diverse and sophisticated hardware. Second, as a hardware/system designer, architecting faster and more efficient systems is challenging as the vast majority of the program's semantic content gets lost in translation with today's hardware-software interface. Moving towards the future, these challenges in programmability and efficiency will be even more intractable as we architect increasingly heterogeneous and sophisticated systems. This thesis makes the case for rich low-overhead cross-layer abstractions as a highly effective means to address the above challenges. These abstractions are designed to communicate higher-level program information from the application to the underlying system and hardware in a highly efficient manner, requiring only minor additions to the existing interfaces. In doing so, they enable a rich space of hardware-software cooperative mechanisms to optimize for performance. We propose 4 different approaches to designing richer abstractions between the application, system software, and hardware architecture in different contexts to significantly improve programmability, portability, and performance in CPUs and GPUs.

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