Increasingly FPGAs are being used to perform signal-processing tasks, particularly in computationally demanding application areas such as video processing and communications. Their massive parallelism often allows FPGAs to handle data rates much higher than what DSPs and general-purpose processors can manage, and in today’s world of rapidly evolving applications and standards FPGAs’ programmability is an advantage over hard-wired solutions. In recent years FPGA vendors have begun to include
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System developers are obtaining more and more of their signal processing software from outside sources, making off-the-shelf software building blocks a vitally important element of the software development process. Figure 1 summarizes the types of software building blocks available today for signal processing applications.
Evolving software demands
Off-the-shelf software building blocks are increasingly popular for a number of reasons. Perhaps the most important reason is that both signal
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Developing a signal processing-based system—like a cell phone or media player—can be a lot of work. Just how much work is a function of many factors, including the complexity of the application, the complexity of the hardware, and, increasingly, the quality of the development tools.
Signal processing applications are getting more complicated, as is the hardware that runs them. Engineers increasingly rely on powerful development tools to help them manage this complexity. These days, “
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Last week three vendors introduced licensable cores targeting consumer audio applications. In the first of these announcements, MIPS announced the MIPS24KEc, the first core to implement the "DSP ASE" signal-processing instruction-set extensions. (For a discussion of these extensions, see the October 2004 edition of Inside DSP.) Although the MIPS24KEc is not specifically tuned for audio applications, MIPS claims that the addition of the DSP ASE provides a 15%-40% boost in performance across a
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System developers often rely on processor benchmarks to gauge system performance. However, the processor is just one of many components that determines overall performance. Fully understanding system performance requires careful analysis of many other elements, such as code-generation tools and third-party software libraries.
Unfortunately, a host of factors can confound attempts to analyze these components. For example, it is difficult to prevent variations in programmer skill and style
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If you are a regular reader of this column, you have probably noticed a recurring theme: signal processing applications are becoming more complicated and more varied—and so is the hardware that runs them. Ten years ago, DSPs used fairly simple architectures, and the architectures of most DSPs were similar to one another. Today, many DSPs use very complex architectures, and there is a remarkable amount of variety among DSP architectures. What's more, DSPs increasingly compete with alternatives
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Last month Cradle introduced the CT3600 family, the successor to its original CT3400 chip. The CT3600 family—which includes the CT3608, CT3612, and CT3616—will offer major improvements over the CT3400 in the areas of parallelism, clock rates, and on-chip integration. Like the CT3400, the CT3600 family will primarily target digital video applications, particularly multi-channel surveillance applications.
The CT3600 will use essentially the same architecture as the CT3400. This heterogeneous
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Last month Freescale added two new parts to its MSC711x family of StarCore SC1400-based DSPs. The two new family members, the MSC7118 and MSC7119, resemble existing family members in most respects. The main difference is that the new parts will operate at 300 MHz—50% faster than the existing 200 MHz parts. Both new chips will also feature 472 Kbytes of on-chip memory, up from a maximum of 408 Kbytes on existing chips. Not surprisingly, the new chips are also more expensive: the MSC7118 and
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At first glance, measuring processor performance on multimedia applications can seem straightforward. Many multimedia applications are based on published standards and widely available software. For example, MPEG-4 video decompression software is available for most popular processors. Because such software is often readily available, measuring multimedia performance may seem to be a simple matter of checking the processor vendor's published performance data for the relevant software modules
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Processor vendors targeting signal processing applications have put a lot of emphasis on compilers over the last few years. Many of the new processor announcements I’ve seen recently stress “compiler friendliness” as one of the main advantages of the new architecture. And vendors like to boast about the enormous amounts of time and money they’ve spent improving their compilers.
Even in the era of gigahertz processors, it is hard to meet demanding performance and cost targets without
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