Each of FlashX components has lightning-fast speed both in memory and on SSDs. FlashR runs R code with performance comparable to the optimized parallel C code.
FlashX components scale beyond memory capacity to graphs with hundreds of billions of edges or matrices of terabytes in a single commodity machine.
FlashX provides simple R programming interface. Parallelization and external-memory data access are completely hidden from users.
A general-purpose programming framework with a vertex-centric programming interface for large-scale graph analysis. FlashGraph is able to scale to billion-node graphs in a single machine and significantly outperforms state-of-art distributed graph analysis frameworks at this scale.
A matrix computation engine that provides a small set of generalized matrix operations to express varieties of data mining and machine learning algorithms. It keeps matrices on SSDs to scale to very large datasets.
An extension of the R programming framework to process datasets at a scale of terabytes with the speed of optimized parallel C code. It provides users a familiar R programming environment to express many machine learning algorithms completely in R.