Amirus Mirror Memory1.4.40

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A Reflective Memory software solution, using standard networking components and the processors own internal exception mechanism. The fault-tolerant design is optimized for low overhead. and delivers throughput of over 30Mbits/second with millisecond latency. Included are comprehensive management and diagnostic utilities, an integrated help facility, a complete API, and numerous example programs.

The entry-level license supports sharing up to 512Kbytes of memory; the full license supports 64Mbyes. Both connect 32 computer systems in a single data network. Multicast techniques and a sophisticated data exchange protocol minimizes the probability of data collision, allowing the system to deliver deterministic performance on Ethernet or wireless networks.

Fault-tolerance is built-in, with a multiple-node caching algorithm designed to ensure memory consistency in the event of node failures on an unreliable network. This permits a robust reflective memory system to be implemented even on wireless networks. The design is peer-to-peer with no single point of failure.

A global lock facility allows cooperating programs to coordinate access to shared memory, making AmirusMM an ideal platform for the rapid development of distributed applications. Locks can be requested at either Shared or Exclusive levels, allowing efficient and protected access to read-only and read-write memory structures.

The system can be integrated with an existing hardware reflective memory ring through a hardware-independent user-written library (available with installation of an additional license). Sections of memory on the hardware side can be mapped into AmirusMM memory, and vice versa. Data exchange between the two rings can be configured to be either exception-driven or periodic, with a data granularity of four bytes.

Simplified MATLAB and VB.NET interfaces are included.

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Users Rating:  
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Downloads last week: 0
Size: 9.23 MB
Price: $100.00
Release Date: 2005-02-18
Publisher: Citrus Controls Inc.
Operating System: windows