Publications
Benchmarking data analysis and machine learning applications on the Intel KNL many-core processor
Summary
Summary
Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product family. KNL has generated significant interest in the data analysis and machine learning communities because its new many-core architecture targets both of these workloads. The KNL many-core vector processor design enables it to exploit much higher...
Learning by doing, High Performance Computing education in the MOOC era
Summary
Summary
The High Performance Computing (HPC) community has spent decades developing tools that teach practitioners to harness the power of parallel and distributed computing. To create scalable and flexible educational experiences for practitioners in all phases of a career, we turn to Massively Open Online Courses (MOOCs). We detail the design...
Benchmarking SciDB data import on HPC systems
Summary
Summary
SciDB is a scalable, computational database management system that uses an array model for data storage. The array data model of SciDB makes it ideally suited for storing and managing large amounts of imaging data. SciDB is designed to support advanced analytics in database, thus reducing the need for extracting...
Enhancing HPC security with a user-based firewall
Summary
Summary
High Performance Computing (HPC) systems traditionally allow their users unrestricted use of their internal network. While this network is normally controlled enough to guarantee privacy without the need for encryption, it does not provide a method to authenticate peer connections. Protocols built upon this internal network, such as those used...
Designing a new high performance computing education strategy for professional scientists and engineers
Summary
Summary
For decades the High Performance Computing (HPC) community has used web content, workshops and embedded HPC scientists to enable practitioners to harness the power of parallel and distributed computing. The most successful approaches, face-to-face tutorials and embedded professionals, don't scale. To create scalable, flexible, educational experiences for practitioners in all...
LLMapReduce: multi-level map-reduce for high performance data analysis
Summary
Summary
The map-reduce parallel programming model has become extremely popular in the big data community. Many big data workloads can benefit from the enhanced performance offered by supercomputers. LLMapReduce provides the familiar map-reduce parallel programming model to big data users running on a supercomputer. LLMapReduce dramatically simplifies map-reduce programming by providing...
Scalability of VM provisioning systems
Summary
Summary
Virtual machines and virtualized hardware have been around for over half a century. The commoditization of the x86 platform and its rapidly growing hardware capabilities have led to recent exponential growth in the use of virtualization both in the enterprise and high performance computing (HPC). The startup time of a...
Enabling on-demand database computing with MIT SuperCloud database management system
Summary
Summary
The MIT SuperCloud database management system allows for rapid creation and flexible execution of a variety of the latest scientific databases, including Apache Accumulo and SciDB. It is designed to permit these databases to run on a High Performance Computing Cluster (HPCC) platform as seamlessly as any other HPCC job...
Big data strategies for data center infrastructure management using a 3D gaming platform
Summary
Summary
High Performance Computing (HPC) is intrinsically linked to effective Data Center Infrastructure Management (DCIM). Cloud services and HPC have become key components in Department of Defense and corporate Information Technology competitive strategies in the global and commercial spaces. As a result, the reliance on consistent, reliable Data Center space is...
Portable Map-Reduce utility for MIT SuperCloud environment
Summary
Summary
The MIT Map-Reduce utility has been developed and deployed on the MIT SuperCloud to support scientists and engineers at MIT Lincoln Laboratory. With the MIT Map-Reduce utility, users can deploy their applications quickly onto the MIT SuperCloud infrastructure. The MIT Map-Reduce utility can work with any applications without the need...