Heterogeneous Cloud Computing
USC/ISI made significant contributions to OpenStack, enabling the first heterogeneous resources (GPUs) and extending the OpenStack resource management model to accommodate specialization. We’ve extended this work to target real-time systems, enabling high performance real-time computing in virtualized cloud environments.
Space Systems Software
USC/ISI developed the system software for the Maestro Processor and is the system software lead for NASA’s High Performance Spaceflight Computing program. In this role, USC/ISI is developing robust operating system support for upcoming many-core and heterogeneous multi-core space processors as well as software-based emulation environments for the processors. Another critical element of our work is the development of software-implemented fault tolerance solutions that will enable future space missions to autonomously self-recover from failures without compromising mission goals.
As a research organization, USC/ISI’s heterogeneous computing group is particularly interested in enabling high performance virtualized computing. This involves optimizations to enable accelerators of all kinds – from GPUs, FPGAs, and Xeon Phi, to high performance SR-IOV-enabled network adapters. USC/ISI is currently working to enable single client 100 GB/s storage performance for combination storage and compute-intensive applications.
USC/ISI’s work in autonomous resource management has led to advances in real-time computing, enabling virtualized resources to vertically scale in order to meet the needs of multi-modal real-time application behavior. This enables improved resource utilization, allowing more efficient resource provisioning with the ability to vertically burst allocate compute performance when needed.