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Compiled and optimized Pixel shader languages are low level and are compiled before being sent to the graphics card That said, Flash Player currently executes Pixel Bender code on the CPU, not the GPU Even so, Pixel Bender kernels run almost as if they were on a graphics card They are executed in parallel, using all available CPU cores and using their instruction sets optimized for vector processing, and they are run asynchronous to the ActionScript Virtual Machine Drawing graphics with Pixel Bender kernels blows the equivalent ActionScript bitmap code (like setPixel()) out of the water in terms of performance, though the gains are most evident on multicore processors..

Architecture-Independent Programming for Wireless Sensor Networks By Amol B. Bakshi, Viktor K. Prasanna Copyright @ 2008 John Wiley & Sons, Inc.

Although these tools are an important part of SPC, they comprise only the technical aspect of the subject. An equally important element of SPC is attitude a desire of all individuals in the organization for continuous improvement in quality and productivity through the systematic reduction of variability. The control chart is the most powerful of the SPC tools.

Pixel Bender kernels are by nature intensive and may bog down even recent computers. Use sparingly.

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Flash Player 10.0 through 10.1 run Pixel Bender kernels on the CPU regardless of the render path, on both mobile and desktop platforms. Future releases may move Pixel Bender kernels onto the graphics card when possible.

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In any production process, regardless of how well-designed or carefully maintained it is, a certain amount of inherent or natural variability will always exist. This natural variability or background noise is the cumulative effect of many small, essentially unavoidable causes. When the background noise in a process is relatively small, we usually consider it an acceptable level of process performance. In the framework of statistical quality control, this natural variability is often called a stable system of chance causes. A process that is operating with only chance causes of variation present is said to be in statistical control. In other words, the chance causes are an inherent part of the process. Other kinds of variability may occasionally be present in the output of a process. This variability in key quality characteristics usually arises from three sources: improperly adjusted machines, operator errors, or defective raw materials. Such variability is generally large when compared to the background noise, and it usually represents an unacceptable level of process performance. We refer to these sources of variability that are not part of the chance cause pattern as assignable causes. A process that is operating in the presence of assignable causes is said to be out of control. Production processes will often operate in the in-control state, producing acceptable product for relatively long periods of time. Occasionally, however, assignable causes will occur, seemingly at random, resulting in a shift to an out-of-control state where a large proportion of the process output does not conform to requirements. A major objective of statistical process control is to quickly detect the occurrence of assignable causes or process shifts so that investigation of the process and corrective action may be undertaken before many

Now that you understand a little bit about how Pixel Bender kernels are run, you can get comfortable with how they re structured. I ll show some Pixel Bender kernel language here, just to get you used to how it looks. I won t focus on syntax, data types, or functions of the language until the section Pixel Bender Kernel Language. A Pixel Bender kernel is, as I ve said, a self-contained program. The program is run, in parallel, once for every output pixel, and the output pixels are reassembled into the output image. A kernel is very much like a class. It can have member variables and functions, but it must always have one main function, called evaluatePixel(), which assigns a result value to a pixel. This way, Pixel Bender knows how to run the kernel and what to do with the output. You specify this like so:

* Some prefer to include the experimental design methods discussed previously as part of the SPC toolkit. We did not do so, because we think of SPC as an online approach to quality improvement using techniques founded on passive observation of the process, while design of experiments is an active approach in which deliberate changes are made to the process variables. As such, designed experiments are often referred to as of ine quality control. The terminology chance and assignable causes was developed by Dr. Walter A. Shewhart. Today, some writers use common cause instead of chance cause and special cause instead of assignable cause.

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