Toward a Hardware/Software Co-Design Framework for Ensuring the Integrity of Exascale Scientific Data
|Principal Investigator:||Sean Peisert (PI)|
|Senior Personnel||Prof. Matt Bishop (UC Davis)
Prof. Sophie Engle (University of San Francisco; Visiting Faculty Affiliate at Berkeley Lab)
|Graduate Student Interns||Bogdan Copos (LBNL/UC Davis)
Anna Giannakou (LBNL/INRIA Rennes)
Scientific data today is at risk due to how it is collected, stored, and analyzed in highly disparate computing systems. How can we make claims about the integrity of data as it traverses open, international networks and via instruments and systems with widely varying reliability and provenance? Numerous causes for integrity loss are possible, including bugs in existing computational pipelines, network events, user error, unintentional system effects or even intentional attack by outsiders (e.g., scientific competitors), insiders (e.g., disgruntled employees), or in the hardware/software supply chain, without any trace of the modification. Given these gaps and shortcomings in existing HPC solutions, how can we make claims about the integrity of the scientific data as it traverses those systems and networks?
We believe that in order to solve the problems described above that future HPC hard- ware and software solutions should be co-designed together with security and scientific computing integrity concepts designed and built into as much of the stack from the outset as possible. Given the risk of data loss due to software and hardware, this should take into account hardware elements, operating systems, compilers, application software, and the networking stack, all the way down to the way in which software developers write software and users interact with systems in a way that can affect scientific computing integrity. However, prior to laying out the research roadmap to design and construct such an architecture, we believe that several important aspects first need to be understood more clearly.
This project takes a broad look at several aspects of security and scientific integrity issues in HPC systems. Using several case studies as exemplars, and working closely with both domain scientists as well as facility staff, we propose to test and validate several initial concepts in existing scientific computing workflows at NERSC DOE HPC facility, and analyze those models better characterize integrity-related computational behavior.
This project is supported by the US Department of Energy's Office of Science's Advanced Scientific Computing Research (ASCR) program.