Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
The development of efficient parallel out-of-core applications is often tedious, because of the need to explicitly manage the movement of data between files and data structures ...
A concurrent partitioner for partitioning unstructured finite element meshes on distributed memory architectures is developed. The partitioner uses an element-based partitioning st...
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
Exploiting locality at run-time is a complementary approach to a compiler approach for those applications with dynamic memory access patterns. This paper proposes a memory-layout ...