ICSA Faculty Talk - 18/12/2018

System design principles for intelligent applications

In this digital age, we are increasingly relying on modern online services and cyber-physical systems that are based on “data-driven intelligence". These intelligent applications require a high degree of reliability, real-time performance, scalability, and security. The state-of-the-art for designing, developing, and deploying such applications follow ad hoc practices, where the application programmers explicitly manage computational resources and application state on a per-application basis. However, such ad hoc practices easily become unmanageable because the underlying computing infrastructure composed of cloud and edge/IoT computing resources is highly heterogenous, and it comes with varying degree of performance, cost, reliability, and security guarantees. Our work aims to build an end-to-end generic system that supports the design, development, and deployment of a wide-range of data-driven intelligent applications, where the application programmers, such as machine learning experts or data scientists, can focus on their core business logic/algorithms, and our system transparently provides all the aforementioned desired functional properties.

More specifically, I will present four system design principles targeting hardware/software co-design for intelligent applications: (1)

Scalability: How to seamlessly support ever growing application workload with increasing number of cores, and at the same time, embracing the heterogeneity in the underlying computing platform. (2) Reliability: How to leverage new ISA extensions to build reliable software systems; (3)

Security: How to build secure systems for the underlying untrusted computing infrastructure using a combination of trusted execution environments (TEEs) and small trusted computing base (TCB); and (4)

Performance: How to achieve real-time performance using incremental and approximate computing paradigms.

As I will show in the talk, we follow these design principles at all levels of the software stack covering operating system, storage/file-system, compiler and run-time libraries, and all the way to building distributed middleware. More importantly, our approach transparently supports existing applications -- we neither require a radical departure from the current models of programming nor complex, error-prone application-specific modifications.