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Dataflow parallel programming language for clusters
PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library.
Also there are available tools for benchmarking cluster interconnect and visualize it.
A collection of performance analysis software that can assist with a variety of techniques useful for application software optimization and benchmarking. The current release provides support for analysis with hardware performance counters on Linux.
OpenJCS (Job Control System) is a batch scheduling and control system for use on Unix systems which uses load balancing, dependency control, scheduling, runbooks, queueing and resource allocation subsystems for unmatched scalability and flexibility.
Trusted by nearly 20,000 customers worldwide, and all major cloud providers.
OpenVPN's products provide scalable, secure remote access — giving complete freedom to your employees to work outside the office while securely accessing SaaS, the internet, and company resources.
The underlayer is a symmetric decentralized parallel computing and load balancing framework, providing c, perl and java APIs for distributed job management.
The Portable Highly Available Sensors (PHASE) project aims at creating an example application that demonstrates the usage of Application Interface Specification service interfaces of the Service Availability Forum.