Engineering topics
Publications and source records attributed to Baskaran, Muthu.
R-Stream version 3.21.3, including its TensorFlow front-end (TFRCC) and LLVM 9 front-end. This version includes the features developed in the Portacy Phase II contract. R-Stream is a source-to-source automatic parallelization engine. For usage, please refer to the manuals (In particular, user guide and release notes) available in the package.
R-stream release 3.22.3 including the Glow and TVM front-ends, and the features developed in the Portacy 2B, X-MAT and STAPL projects. R-Stream is an automatic parallelization, source-to-source compiler. The TVM and Glow front-ends to R-Stream were developed to automatically map neural net models to parallel computers using openMP and CUDA (for Glow).
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ENSIGN is a data analytics software package offering a modern unsupervised machine learning solution for scalable discovery in Big Data. The analytics in ENSIGN are based on an advanced mathematical tool called tensor decomposition and they are optimized to run efficiently on a range of computing platforms (from small multicore Desktop platforms to large Supercomputing clusters and novel high-end memory-driven computing platforms such as HPE Superdome Flex). ENSIGN enables the user to extract deep insights from the entirety of massive-scale (100s of Gigabytes or Terabytes scale) multidimensional data. ENSIGN uncovers latent patterns in data without the user having to specify or describe what the patterns are; the user, in the first place, may not even know such patterns existed and that they have to look for such patterns. The insights gained from ENSIGN could be trailheads that can be used as starting points for deeper forensic investigation.
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