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Hybrid strategies require software task execution and fixed hardware to execute complex time-consuming tasks usually the Fuzzy inference process (FIP) [15].
Co-verification changes this environment by using a virtual prototype of the hardware to execute the software well before prototypes are available.
It relies on a post-compiler to extract the p-thread code from program binaries and uses custom- designed hardware to execute the p-thread.
When it comes to inference — the machine learning processes that happen on the hardware to execute some kind of action, like image recognition, based on trained models — Zhang said the chipsets would support it, but he would not comment further.
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In that regard, Canonical is working with hardware partners to execute Ubuntu TV.
We discuss specialized hardware being able to execute such a search in a fully parallel manner.
Running time refers to the time that the whole parallel hardware platform takes to execute a parallel program and solve a problem.
For implementation of these highly-demanding applications, highly-optimized application-specific multi-processor system-on-a-chip (MPSoCs) are required involving hardware multi-processors to execute the critical computations.
For the tasks implemented on the RCU, we assume that the hardware resources are sufficient to execute in parallel all hardware tasks chosen by the partitioning step.
There are very few limits on what custom tasks may do: Vadaparty [ 36] describes a custom-task set for WWF created at Merrill Lynch that invokes multiprocessor parallel hardware over a network to execute complex finance-related tasks in a manner transparent to the non-programmer workflow author.
When MicroBlaze sends a signal to the hardware module, it can then continue to execute other tasks until the hardware module writes back the results to the DDR3-SDRAM and sends a signal to notify the processor.
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CEO of Professional Science Editing for Scientists @ prosciediting.com