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来源:LM317 Electronics Components编辑:FEIG ELECTRONIC时间:2021-06-15 15:15:54

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For more details on the requirements of video codecs and pre- and post-processing algorithms, see Squeeze Play: How Video Compression Works”.

Audio Codec RequirementsMost video applications include audio. As shown in Table 3, audio codecs are generally much less demanding than video codecs in terms of computational power and memory bandwidth requirements. Audio codecs also have smaller memory footprints and are easier to program than video codecs.

LNK2V392MSEGBN_Datasheet PDF

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As with video codecs, the computational load of most audio codecs is asymmetric—encoding is more computationally demanding than decoding, typically by a factor of two or more. In addition, audio coders are much more complicated and require far more memory bandwidth than audio decoders.

Input/OutputThe input/output (I/O) software component manages the movement of data between peripherals and the other software components. The processing load and memory footprint of I/O software is typically small. However, as digital video products grow more complex, so too do the protocols and standards for connecting them. This results in greater I/O hardware and software complexity. For example, the software stack” for an Ethernet interface is far more complex than the stack for a simple three-wire serial port.

LNK2V392MSEGBN_Datasheet PDF

Operating SystemThe operating system (OS) provides and controls access to basic services and resources used by the application. Example services include inter-process communications and scheduling of tasks. Example resources include memory (supported via memory management functionality) and I/O devices (supported via device drivers).

An OS is expected to contribute only a small percentage of the overall computational load of a complete application. However, as the complexity, capability, and flexibility of an OS increases, so too does its memory footprint. The memory footprint can range from a few kilobytes to several tens of megabytes.

LNK2V392MSEGBN_Datasheet PDF

As with DRM software, availability is a key consideration for OSs. It is usually impractical for a system designer to port an OS to a new processor. If system designers wish to use a particular OS, they must consider whether candidate processors already support this OS.

Processor Selection MethodologyFor many digital video product developers, development schedules are short and profit margins are thin. Selecting a processor that best fits the product's needs is critical to the success of the product. Processor selection is difficult, though, because the field of processors options is large and rapidly changing.

OptimoDE is a framework that includes a configurable VLIW-styled architecture, from which specific data engines are derived, a comprehensive set of hardware configuration tools, a powerful C compiler, reference examples and an AMBA interface kit.

The data engine consists of datapath units that are pieced together in drag-and-drop fashion to execute the target algorithm. These functional datapath units include generic arithmetic and logical units, storage, and interconnect. Other specialized functions include butterfly and DCT engines. Users can extend and customize datapath units to meet application-specific processing needs.

OptimoDE tools also include a C-compiler optimized for the architecture. Providing the compiler ensures that hardware and software are optimized together.

The design team starts with a C/C++ specification for the algorithm, which is, generally speaking, the most straightforward way to specify an algorithm. Then, a data-engine template is chosen—a single ALU, single multiplier and single RAM block with a global bus and merged memory and address registers, for example.

Using the template and the ARM configuration tools, the design teams configure the architecture to meet the specified performance requirements, adding other blocks as needed. OptimoDE software is capable of extracting parallelism from the algorithm and this helps the design team significantly. Low-power optimization techniques are also built into the tools. The process is iterative. The various parameters of the architecture are tweaked and the result profiled against the performance goals, which typically consist of a cycle budget and a power budget.

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