Reseach Interests
Security in HPC Clusters
Existing security mechanisms for high-performance and distributed computing infrastructure are complex and difficult to deploy. As a result, many high-performance and distributed computing facilities do no deploy sufficient security mechanisms. This has prevented privacy-sensitive applications, such as those in the medical fields, and security-sensitive applications from using such facilities. In this project, we will develop and deploy DICE, Data Insurance in the Cluster Environment, to enhance the security in HPC and distributed computing clusters. DICE will consist of three major components: a container-based virtual cluster, a component to defend against side-channel attacks, and a secure execution ledger for auditing. The container-based virtual cluster will be developed based on the Docker Linux container. The Docker security mechanism will be enhanced by deploying an effective key management scheme for groups and by reducing the attack surface exposed to containers. Novel defence mechanisms will be developed and deployed to defend against side-channel attacks in the cluster environment by exploiting new security features in the recent processors. The secure execution ledger will provide a global holistic view of program execution in the whole system, enabling auditing the behavior of individual user as well as user groups. DICE essentially creates a two-level security model: on the (physical) cluster level, a group of (mostly) mutually trusted users share a single virtual cluster for their jobs; and inside the virtual cluster, the group may use existing security mechanisms of their software-of-choice to further refine security.
GPU Computing
The use of a GPU (graphics processing unit) together with a CPU to accelerate general-purpose scientific and engineering applications. Pioneered five years ago by NVIDIA, GPU computing has quickly become an industry standard, enjoyed by millions of users worldwide and adopted by virtually all computing vendors. GPU computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user's perspective, applications simply run significantly faster. CPU + GPU is a powerful combination because CPUs consist of a few cores optimized for serial processing, while GPUs consist of thousands of smaller, more efficient cores designed for parallel performance. Serial portions of the code run on the CPU while parallel portions run on the GPU.
Docker
Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers allow a developer to package up an application with all of the parts it needs, such as libraries and other dependencies, and deploy it as one package. By doing so, thanks to the container, the developer can rest assured that the application will run on any other Linux machine regardless of any customized settings that machine might have that could differ from the machine used for writing and testing the code.
Last update: 05/01/2020