Feature:
1) PUSHvm handles large numbers of data stream connections
2) PUSHvm achieves infinite scalability (multi-core parallelism)
How:
PUSHvm is coded for an indefinite number of cores vs. a fixed number of cores.
Result:
PUSHvm can handle large numbers of data stream connections, is infinitely scalable, and effectively utilizes modern multi-core machines.*
*uCirrus has invested in multi-core technology first and foremost (vs. multi-server) because this is the direction and future of the microprocessor industry. PUSHvm will enable you to run on fewer servers.
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Feature:
3) PUSHvm processes high volumes of data with rapid response time (low latency)
4) PUSHvm performs data computation in real-time (sort / search / analytics)
How:
PUSHvm divides tasks into sub-tasks and processes them in parallel through multi-cores. Each sub-task works on data in the cache independently in a cooperative manner. Processes in streaming mode vs. batch mode
A: High-volume data stream ingest
B: Task components are divided into “sub-tasks”
B & C: Sub-tasks are processed in parallel through the cores
C: Task components are reunited
D: Data is “PUSHED” or broadcast
Result:
PUSHvm processes high volumes of data and performs computation at high speed with rapid response time (low latency).
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Feature:
5) PUSHvm “broadcasts” or PUSHES information to one or many audiences or systems or devices
How:
- PUSH 1.0: broadcast of data to one or many audiences or systems or devices
- PUSH 1.1: private, customizable data channel – broadcast to one or many audiences or systems or devices
- PUSH 1.2: as large audiences and entities act upon data, it becomes part of the data stream again in what can be envisioned as a sort of bidirectional and interactive feedback loop
Result:
PUSHvm's PUSH broadcast capabilities enable interactive, customizable, bidirectional, real-time poll-less data communications.
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