Widespread adaptation of shared memory programming for High Performance Computing has been inhibited by a lack of standardization and the resulting portability problems between pl...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
Shark is a research data analysis system built on a novel rained distributed shared-memory abstraction. Shark marries query processing with deep data analysis, providing a unifie...
Cliff Engle, Antonio Lupher, Reynold Xin, Matei Za...
On a distributed memory machine, hand-coded message passing leads to the most efficient execution, but it is difficult to use. Parallelizing compilers can approach the performance...
Scalability of parallel architectures is an interesting area of current research. Shared memory parallel programming is attractive stemming from its relative ease in transitioning...
Umakishore Ramachandran, Gautam Shah, Ravi Kumar, ...