Stream Processor: Programmability with efficiency

For many signal processing applications programmability and efficiency is desired. With current technology either programmability or efficiency is achievable, not both.
Conventionally ASIC's are being used where highly efficient systems are desired. The problem with ASIC is that once programmed it cannot be enhanced or changed, we have to get a
new ASIC for each modification. Other option is microprocessor based or dsp based applications. These can provide either programmability or efficiency. Now with stream processors we can achieve both simultaneously. A comparison of efficiency and programmability of Stream processors and other techniques are done. We will look into how efficiency and programmability is achieved in a stream processor. Also we will examine the
challenges faced by stream processor architecture.

The complex modern signal and image processing applications requires hundreds of GOPS (giga, or billions, of operations per second) with a power budget of a few watts, an efficiency of
about 100 GOPS/W (GOPS per watt), or 10 pJ/op (Pico Joules per operation). To meet this requirement current media processing applications use ASICs that are tailor made for a
particular application. Such processors require significant design efforts and are difficult to change when a new media processing application or algorithm evolve. The other alternative to meet the changing needs is to go for a dsp or microprocessor, which are highly flexible. But these do not provide the high efficiency needed by the application. Stream processors provide a solution to this problem by giving efficiency and programmability simultaneously. They achieve this by expressing the signal processing problems as signal flow graphs with streams flowing
between computational kernels. Stream processors have efficiency comparable to ASICs (200 GOPS/W), while being programmable in a high-level language. We will discuss how stream processor is achieves programmability and efficiency at the same time. Also we will look at the tools available for design of stream processing applications and challenges faced in this
approach to media processing.