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But the simulation is done using software where you can see what the individual registers are doing before you put the design into the FPGA. Most developers use what is called a testbench as a tool to verify that the FPGA will work when attached to the real world. A testbench can be a mix of software simulation and actual hardware — designed by you — that makes up a model of the system that will contain your FPGA.
Instead, a testbench focuses on the most meaningful gates that contain the critical areas of your design. Simulation environments help you to isolate particular areas and add debugging aids in those areas so you can get your design working the way you want. Any good software application requires extensive documenta- tion that tells the customer or end-user exactly how the appli- cation is defined, and brings up any caveats, warnings, and so on. The documentation requirements are the same for FPGAs as in any microcontroller-based programming; of course, the contents will differ greatly.
Like any system, if the hardware is correct, the design can evolve to include bug fixes and feature enhancements. Trying out the design in the system Once the design is programmed into the hardware, ensure that everything works as it is supposed to. What does work- ing really mean for an FPGA?
This stage is sometimes called closure. And, as with any hardware device, certain perfor- mance criteria are expected. In many applications, power consumption is an important design criterion. Think of your smartphone, for example. Smartphones have strict power requirements so that they can maintain an acceptable battery life. Speed is another important criterion. Test to ensure each net wire connection between gates meets its timing limit.
Finally, ensure that every clock and power pin is connected on your FPGA. Then, while the design is still in software and easy to test, you can verify that it works as expected, that it works at the required speed, and you can even estimate how much power the design will consume.
Now comes the magic: You can load your tested design into the target FPGA on your prototype board, power up the system, and verify that everything is working as expected.
You now have custom hardware to exactly fit your requirements — months before you would receive the first sample chips of an ASIC. In this chapter, I examine the concept of an electronic system.
Figure shows the traditional model of system design. The diamond shapes you see between each block represent decision points in the process. Figure System design with decision points.
This question appears during the requirements definition phase and is the fun- damental question. The answer to this question is often provided by the product manager in coordination with the customer and drives the requirements gathering phase.
Often, an existing system design is in place that, with some changes, may meet the requirements of the system. This is an important question asked during the design and implementation phase.
The amount of the system that can be left in software determines what types of hard- ware can be used. FPGAs and microcontrollers can be used to program the software. Many times, a functional block of your system design may already be implemented in a commercially available hardware device known as off-the-shelf.
In Figure , you can see that during the requirements defini- tion, designers must consider the constraints on their design, such as performance, power consumption, and size. The functions of the system are also important — including which functions are visible, invisible, or locked.
Finally, designers run experiments on their design. This process leads to early system estimation, which indicates the actual size and scope of the system and what it will take to implement. Figure Defining system requirements. The design process for FPGAs is an iterative one — you start with an idea of the system and then refine the idea into definitions of transactions. A transaction would include input, processing, and output.
You can think of a transaction just like a bank transaction where you hand money over to the teller, the teller takes the money, and then adds the money to your account. Basically, a transaction is anywhere in the system where information is shared between two components of the system.
After you define the transactions, you implement them, and then verify that they work and meet the functions and con- straints you established at the start. This is another iterative process that requires deciding which functions will be done in hardware and which in software, which can be done with existing IP, and which will have to be newly written.
In fact, you may have driven this system to work this morning. Infotainment Infotainment is a nifty word used to describe the information and entertainment systems in automobiles. There is sometimes also a digital video system that will keep your kids happy during those long road trips! There are also common safety features like window and door lock controls that keep your children from opening doors and windows while the car is in motion.
Driver assistance Driver assistance includes some of the coolest technology that has come along in automotive design in recent years. It makes cars safer than ever! Importance of FPGAs Today, most automotive systems depend on low-cost micro- controllers that operate at the point of sensing or action. The trend in automotive design is for consolidation of systems and for systems to become more autonomous.
As systems become more sophisticated, their processing and memory require- ments skyrocket. Consider sensor fusion with Kalman filters. Sensor fusion is the combining of sensory data from disparate sources so that the resulting information is better than what would be obtained from these sources individually, such as stereoscopic vision the calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints.
Kalman filters are commonly used for guidance, navigation, and control of vehicles. As automobile systems consolidate, microcontrollers are being absorbed into SoC implementations. In order to control the explosive growth in the number of models, changes during the model year, evolution in bus architectures, and the continuous demand for better security, the trend is moving toward SoC FPGAs being the only viable answer to solve these design chal- lenges and needs for frequent updates.
The car is only one example of how systems become more dependent on electronics, the electronics become more com- plex and change more rapidly, and the need grows for SoCs that can change even during a model year.
This same pattern shows up across a huge range of products with complicated behavior, from aircraft and trains to electric power grids to even home appliances. Yes, even your toaster. This chapter walks you through why heterogeneous computing is necessary and the emergence of new languages for creating software to execute on them.
Heterogeneous Computing Inside data centers, one of the major trends is a shift in the com- puting architecture: from multicore CPUs to heterogeneous com- puting. Heterogeneous computing refers to systems that use more than one type of processor to perform specialized processing capabilities.
An example of a heterogeneous computing system is a graphics rendering system that uses a CPU and a graphics processing unit GPU to render 3D graphics on a computer. GPUs are especially adept at rendering 3D scenes and perform- ing mathematically intensive computations on large datasets. Heterogeneous computing is becom- ing more of the standard as systems consolidate and must incor- porate several different processor architectures.
Parallel computing is the capability of computers to perform many calculations simultaneously based on the principle that large problems can be broken down into smaller problems and then solved concurrently in parallel.
Parallel comput- ing comes in many different forms: bit-level, instruction level, data, and task-based. As power consumption has become more of a design factor in embedded electronics, parallel computing has become the dominant paradigm in computer architecture, most commonly seen in the form of multicore processors. Data parallelism focuses on the idea of separating data across multiple processors so that it can execute in parallel.
Multicore processors often do this by farming out multiple instances of a program to each of the processors to execute these instructions simultaneously. Task parallelism has to do with a processor farming out computer code blocks known as threads across different processors to execute in parallel.
The need for heterogeneous computing is leading to new pro- gramming languages to exploit the new hardware. OpenCL includes a language for develop- ing kernels functions that execute on hardware devices as well as application programming interfaces APIs that allow a main program to control the kernels.
OpenCL allows for parallel computing using task-based and data-based parallelism. In the last decade or so, processor hardware frequencies have hit a so-called power wall, which prevents higher frequen- cies from being achieved on processors.
Chapter 4: The Future: Heterogeneous Computing and OpenCL 33 enhancing their instruction sets so several instructions can execute at the same time, speeding up program execution without requiring faster clock frequencies to do so. Software companies have been busy as well, developing software that allows chunks of computer code known as threads to execute in true parallel fashion. FPGAs give you an alternative to the typical data or task parallelism by also offering pipeline parallelism where tasks can be spawned in a push-pull configuration with each task taking data from the previous task with or without host interaction.
OpenCL allows you to develop your code in the familiar C programming language. Then, using the additional capabilities provided by OpenCL, you can separate your code into normal software and kernels that can execute in parallel.
OpenCL keeps you at a higher level of programming, making your system open to more software developers. Code reuse is often an elusive goal for software developers and system designers. OpenCL kernels allow for portable code that you can target for different families and generations of FPGAs from one project to the next, extending the life of your code.
The field-programmable part is now sometimes less than half of the chip area. This chapter highlights how FPGAs are used in several areas of industry and technology. Single-Device Motor Control Motors and motor control are commonplace in any industrial design. Most motor con- trol systems are designed with microcontroller technology. However, microcontrollers can fall short of the performance demands of sophisticated motor-control algorithms such as direct torque control DTC or sensorless field oriented control SFOC , for example.
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