Title: SpaceCubeX: Emulation Results of Hybrid On-board Processing Architectures
Presenting Author: Matthew French
Organization: USC/ISI
Co-Author(s): Andrew Schmidt, Gabe Weisz, Tom Flatley, Gary Crum, Jonathan Bobblit, Carlos Villalpando, Robert Bocchino

Abstract:
The SpaceCubeX project addresses NASA Earth Science missions and climate architecture plan and its underlying needs for high performance, modular, and scalable on-board processing. Next generation missions are specifying instruments with significantly increased temporal, spatial, and frequency resolutions and moving to global, continuous observations. These goals translate into on-board processing throughput requirements that are on the order of 100-1,000x more than previous Earth Science missions for standard processing, compression, storage, and downlink operations. SpaceCubeX addresses these needs, by researching and developing a Hybrid Multi-core CPU/FPGA/DSP Flight Architecture. Recent studies have shown that in order to realize mission size, weight, area, and power (SWAP) constraints while meeting inter-mission reusability goals, compact heterogeneous processing architectures are needed. In a heterogeneous architecture, general OS support, high level functions, and coarse grained application parallelism are efficiently implemented on multi-core processors, while a co-processor provides mass acceleration of high throughput, fine-grained data parallelism operations, to achieve high performance robustly across many application types. SpaceCubeX provides a structured approach to assess and develop hybrid architectures, fundamentally changing the avionics processing architecture development process. This presentation provides a summary of the efforts, in which the emulation spiral of research and development was completed. Here 6 different different heterogeneous board architectures have been represented in our framework, and over 300 benchmark applications have been collected, where hybrid computing has shown up to a 20,000x increase in processing performance over the current state of practice.