2:05 PM - 2:50 PM
Room: Elwha Ballroom
Chair:
Rich Vuduc, Georgia Institute of Technology, U.S.
The last decade has seen a paradigm shift in the architecture of computing platforms, with a trend toward combining general-purpose processors and specialized accelerators. For example, GPUs have made a significant impact in both the hardware industry and the application domain, as has been seen from the recent development of machine learning applications. Other platforms such as Processing-In-Memory and FPGA-based reconfigurable architectures have regained attention, and with these special accelerators, the computing platforms become more heterogeneous. These heterogeneous architectures are especially attractive because they can provide high performance and energy efficiency for both general-purpose applications and high-throughput applications. Thus, from IoT devices to server processors, heterogeneous architectures have become increasingly popular. However, these heterogeneous architectures introduce several new challenges, including programmability issues and designing the hardware architecture in a way that can maximally exploit the underlying heterogeneity. To address these issues, a wide variety of modeling has been used including analytical, regression based, and cycle-level. In this talk I will discuss how different modeling techniques have been addressed and how they can be helpful to guide architecture studies and software optimizations.
Hyesoon Kim
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