Publications
Scalable cryptographic authentication for high performance computing
Summary
Summary
High performance computing (HPC) uses supercomputers and computing clusters to solve large computational problems. Frequently HPC resources are shared systems and access to restricted data sets or resources must be authenticated. These authentication needs can take multiple forms, both internal and external to the HPC cluster. A computational stack that...
Driving big data with big compute
Summary
Summary
Big Data (as embodied by Hadoop clusters) and Big Compute (as embodied by MPI clusters) provide unique capabilities for storing and processing large volumes of data. Hadoop clusters make distributed computing readily accessible to the Java community and MPI clusters provide high parallel efficiency for compute intensive workloads. Bringing the...
Dynamic Distributed Dimensional Data Model (D4M) database and computation system
Summary
Summary
A crucial element of large web companies is their ability to collect and analyze massive amounts of data. Tuple store databases are a key enabling technology employed by many of these companies (e.g., Google Big Table and Amazon Dynamo). Tuple stores are highly scalable and run on commodity clusters, but...
Benchmarking the MIT LL HPCMP DHPI system
Summary
Summary
The Massachusetts Institute of Technology Lincoln Laboratory (MIT LL) High Performance Computing Modernization Program (HPCMP) Dedicated High Performance Computing Project Investment (DHPI) system was designed to address interactive algorithm development for Department of Defense (DoD) sensor processing systems. The results of the system acceptance test provide a clear quantitative picture...