HPCC (High Performance Computing Cluster) stores and processes large quantities of data, processing billions of records per second using massive parallel processing technology. Large amounts of data across disparate data sources can be accessed, analyzed, and manipulated in fractions of seconds. HPCC functions as both a processing and a distributed data storage environment capable of analyzing terabytes of information.
|Tags||High Performance Computing Big Data Parallel processing Super Computing Computer Cluster Parallel Computing Data Intensive Computing|
|Licenses||Commercial Apache License 2.0|
|Operating Systems||Linux 64 bit|
New Blog Series from Chief Data Scientist, David Bayliss, on graph processing and the new Knowledge Engineering Language, KEL. http://hpccsystems.com/blog/adventures-graphland-part-i
Release Notes: This latest version includes the same release notes as CE 4.2.2 as well as bug fixes and patch builds.
Release Notes: This is a maintenance release which includes updates and issue fixes.
Release Notes: The HPCC Systems Platform Release Candidate is now available. Changes include memory leak fixes, ECL Watch updates, minor clarifications in DOCs, and other miscellaneous bugfixes.
Release Notes: This release adds ECL visualizations (including a new cellFormatter bundle), improvements to ECL Watch Technical Preview, an ECL Plugin for Eclipse's new features, a Roxie Monitoring Tool (Ganglia) Technical Preview which leverages Ganglia, an Open Source, scalable, distributed monitoring system to produce a graphical view of a Roxie cluster's servers , package map improvements, GROUP JOIN and LOOKUP JOIN improvements, and much more.
Release Notes: This release contains updates and fixes from the prior version. Changes include, but are not limited to, documentation updates to JVM settings, Configmgr, Automate Eclipse Help, support for CentOS builds with the -with-plugins variant, clarification of ECL bundle parameter documentation, and more.