4 projects tagged "Parallel processing"
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.
RunJRun is a very simple system for doing parallel processing in Java, using Amazon Elastic Compute Cloud (EC2) instances as compute nodes. The basic compute unit is a Runnable, Serializable Java object, a "task" for short. A user submits a list of such tasks to RunJRun. Each task then has its run() method invoked on an EC2 instance. To use it, you'll need an Amazon Machine Image (AMI) that has the RunJRun server-side software installed; several such AMIs are available.
FastFlow is a pattern-based programming framework targeting streaming applications. It implements pipeline, farm, divide and conquer, and their composition, as well as generic streaming networks. It is specifically designed to support the development and the seamless porting of existing applications on multi-core. The layered template-based C++ design ensures flexibility and extendibility. Its lock-free/fence-free run-time support minimizes cache invalidation traffic and enforces the development of high-performance (high-throughput, low-latency) scalable applications. It has been proven faster than TBB, OpenMP, and Cilk on several micro-benchmarcks and real-world applications, especially when dealing with fine-grained parallelism and high-throughput applications.