The Modelling and Optimising Complex Heterogeneous Architecture (MOCHA) project at the University of York aims to equip the Huawei 5G base stations with increased real-time capabilities (i.e., the response time can be bounded in the worst case), reduce latency and improve throughput, to serve the emerging applications in the domains of industrial automation, highly automated driving, and robotics under ultra-reliable low-latency communication (uRLLC) mixed with other types of traffic. The keys to achieve these objectives lie on both the scheduling and memory levels.

Considering a multi-core architecture as is in the Huawei 5G base station, resource management plays the central role. Simple scheduling heuristics to keep the cores busy may lead to long average- and worst-case latency. We will propose scheduling and allocation mechanisms towards more efficient resource utilisation and improvement on the worst case, together with static analysis to tightly bound the response time, as well as digital twin to explore the system and perform statistical evaluation.

This research project is funded by Huawei Technologies Co., Ltd with a funding value of £985,927, covering three years from December 2019 to December 2022.

Research Roadmap

MOCHA has a wide range of research novelties in the context of multicore research:

MOCHA Toolchain

The MOCHA Toolchain (MOCHA-T) aims to provide a collection of simulation and analysis tools to facilite multicore scheduling research. The MOCHA-T includes the following modules:

Project Members

Workshops / Seminars

Publications

  1. Shuai Zhao, Zhe Jiang, Xiaotian Dai, Iain Bate, Ibrahim Habli, Wanli Chang. Timing-Accurate General-Purpose I-O for Multi- and Many-Core Systems: Scheduling and Hardware Support. Design Automation Conference (DAC). 2020