Advanced Memory Optimization Techniques for Low Power Embedded Processors

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There are various contributions in the embedded systems. NAND flash is used as the second storage literature that differ in the number of hierarchy levels that are to store user data. Different from DRAM-based main memory, dimensions in the design space. Some works focus on cache this hybrid main memory can store code and even user data by memories such as [14], [15], [16], [17] and [18], while [19] utilizing the non-volatility of PCM.

Different physical partitioning are proposed by Lee and Tyson [21] and Benini et al. The idea behind these approaches has been extended by Grun et al. The system architecture with the application-specific hybrid [24]. An alternative allows reconfiguration in both its size and associativity. This solution does not just imply the Architecture for Run-Time reconfiguration Smart cache. There are two complementary circuits solutions explicitly for performance optimization may also used in parallel that perform the mapping, allowing the address help in reducing energy.

Techniques that attempt to reduce the to be routed to the correct set and way. As the cache size and cache-miss rate by proper cache design are an example of such associativity varies, so does the number of bits needed for the solutions; in fact, cache-miss reduction decreases the effective tags. In their architecture, they store the maximum sized tag for average cost of accessing memory data. Organization of the Smart cache architecture.

Varying the cache size through the set selection circuits is performed in parallel with altering the associativity through the way selection logic [27]. Artes et al. Using more CPU time allows us to apply much outlining their comparative advantages, drawbacks, and trade- stronger algorithms to tackle optimization challenges. The architectural classification that is presented in this paper has the advantage of clearly exhibiting lesser explored Wolf and Kandemir [3] provide a taxonomy of variables techniques, and hence providing hints for future research on related to memory systems and embedded system software.

This work addresses enhancements that deal with the relating to memory system analysis and synthesis for architectural aspect of the system. These enhancements look at embedded system software. In this work, they surveyed two aspects: the energy consumption of the memory embedded software techniques showing that software design architecture and the access time delay to the memory space. In the first group are the Incompatible Loop-Nest Organization and Instruction Fetch techniques that modify program access pattern, memory layout and Decode Improvements.

Many embedded applications from image and video processing domain focus on loop nests and arrays of B. Software optimizations signals. Among the most popular loop transformations are loop In this section we survey some software optimizations in permutation and loop fusion [3]. Loop permutation changes the order of the loops in a given According Wolf and Kandemir [3] we have several nest.

For example, consider the following code at Fig. Second, we generally Fig. Jacobi iteration code from an image processing application [3]. Because real-time deadlines require global analysis, Note that, for a fixed value of the J loop, the successive we have to have all the software that can affect those deadlines iterations of the inner I loop in this code access elements from in order to be sure that the deadlines are met.

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As a result, we different rows, and this occurs for each reference in the loop can optimize the entire software package rather than body. An optimizing compiler can transform this code to obtain independently optimizing the pieces. Huang et al. Jacobi iteration code transformed [3]. In this paper, the authors use register different references can access different rows.

Therefore, we allocation based on the graph coloring framework. The can expect a much better data locality behavior from this approach proposed in this paper is named Algorithm PRS. Table I presents the number of write activities under different approaches. Note that non-integral writes in the table are Loop permutation belongs to a set of unified class of caused by the branch frequencies of the program. The rows transformations called unimodular transformations.

As represents the best write reduction of different approaches. Code fragment before loop permutation [3]. Given a small-capacity cache, this fragment can read each element of arrays A and B into cache twice, once for each loop. Code fragment after loop permutation [3].

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An advantage of loop transformations is the strong theory References [3], [13] and [29] provide a good overview of behind it and a number of robust implementations from the optimization techniques that are related to the software academia and industry. Another advantage is that each nest in aspect. In fact, Panda et al. These drawbacks of loop transformations motivated researchers to investigate alternative optimizations.

This survey Acevedo [29] showed the importance of each kind of covered both hardware and software approaches. First they instruction on the energy consumption of the system. As each examine architecture-independent optimizations in the form of instruction of a given program activated specific parts of the code transformations. Next, they cover a broad spectrum of microprocessor, the election of the correct instruction could optimization techniques that address memory architectures at generate a reduction of the energy consumption.


NVMs have many benefits that are useful for has tried to rectify both these problems by developing more embedded systems. They are non-volatile, so data kept in the detailed performance models and by analyzing and optimizing NVMs will be retained even after the device is shutdown, for power consumption.

While codesign research is much less allowing short start-up times. Since power is not necessary to mature than scientific compilers, those results point to some keep data in NVMs, their static power consumption is very promising directions for research. One added degree of low.

Other benefits include low- can be changed as an alternative or complement to software cost, shock-resistivity, and radiation tolerance allow NVM to optimizations [3]. Application-specific optimizations [14] C. Su and A. Many works provide some application-specific optimizations that reduce memory energy consumption. Kamble and K. Shafique et al. Ko, P. Balsara and A. Nanda, "Energy optimization of on-chip video memory for Multiview Video Coding. Zatt et al. Other works are related to this topic, such as [32], [33] Trans. VLSI Syst, vol. Bahar, G. Albera and S.

Manne, "Power and performance IV. This paper has presented a survey of memory optimization [18] W. Shiue and C. Chakrabarti, "Memory exploration for low power, techniques for embedded systems. Columeri and D. Thomas, "Memory modeling for system some notes about memories. Juan, T. Lang and J. Lee and G.

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Benini, A. Macii and M. Poncino, Memory Design Techniques for systems.

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Aliagas and M. Grun, N. Dutt and A. Nicolau, "Access pattern based local memory [1] P. Wolf and M. Fevereiro Ge, H. Lim and W. Wong, "Memory Hierarchy Hardware- [26] Z. Shao, Y. Liu, Y. Chen and T. Sundararajan, T. Jones and N. Artes, J.

Embedded system

Ayala, J. Huisken and F. Catthoor, P. Raghavan, A. Lambrechts and M. Hennessy and D. Verma and P. Marwedel, Advanced memory optimization [30] M. Shafique, B. Zatt, F. In certain applications, where small size or power efficiency are not primary concerns, the components used may be compatible with those used in general purpose x86 personal computers. Boards such as the VIA EPIA range help to bridge the gap by being PC-compatible but highly integrated, physically smaller or have other attributes making them attractive to embedded engineers.

The advantage of this approach is that low-cost commodity components may be used along with the same software development tools used for general software development. Systems built in this way are still regarded as embedded since they are integrated into larger devices and fulfill a single role. Examples of devices that may adopt this approach are ATMs and arcade machines , which contain code specific to the application. When a system-on-a-chip processor is involved, there may be little benefit to having a standardized bus connecting discrete components, and the environment for both hardware and software tools may be very different.

One common design style uses a small system module, perhaps the size of a business card, holding high density BGA chips such as an ARM -based system-on-a-chip processor and peripherals, external flash memory for storage, and DRAM for runtime memory. The module vendor will usually provide boot software and make sure there is a selection of operating systems, usually including Linux and some real time choices. These modules can be manufactured in high volume, by organizations familiar with their specialized testing issues, and combined with much lower volume custom mainboards with application-specific external peripherals.

Implementation of embedded systems has advanced so that they can easily be implemented with already-made boards that are based on worldwide accepted platforms. These platforms include, but are not limited to, Arduino and Raspberry Pi. A common array for very-high-volume embedded systems is the system on a chip SoC that contains a complete system consisting of multiple processors, multipliers, caches and interfaces on a single chip.

Embedded systems talk with the outside world via peripherals , such as:. As with other software, embedded system designers use compilers , assemblers , and debuggers to develop embedded system software. However, they may also use some more specific tools:. As the complexity of embedded systems grows, higher level tools and operating systems are migrating into machinery where it makes sense.

For example, cellphones , personal digital assistants and other consumer computers often need significant software that is purchased or provided by a person other than the manufacturer of the electronics. Embedded systems are commonly found in consumer, cooking, industrial, automotive, medical applications. Household appliances, such as microwave ovens, washing machines and dishwashers, include embedded systems to provide flexibility and efficiency. Embedded debugging may be performed at different levels, depending on the facilities available.

The different metrics that characterize the different forms of embedded debugging are: does it slow down the main application, how close is the debugged system or application to the actual system or application, how expressive are the triggers that can be set for debugging e. Unless restricted to external debugging, the programmer can typically load and run software through the tools, view the code running in the processor, and start or stop its operation. The view of the code may be as HLL source-code , assembly code or mixture of both. Because an embedded system is often composed of a wide variety of elements, the debugging strategy may vary.

For instance, debugging a software- and microprocessor- centric embedded system is different from debugging an embedded system where most of the processing is performed by peripherals DSP, FPGA, and co-processor. An increasing number of embedded systems today use more than one single processor core. A common problem with multi-core development is the proper synchronization of software execution.

Real-time operating systems RTOS often supports tracing of operating system events. A graphical view is presented by a host PC tool, based on a recording of the system behavior. The trace recording can be performed in software, by the RTOS, or by special tracing hardware. RTOS tracing allows developers to understand timing and performance issues of the software system and gives a good understanding of the high-level system behaviors.

Embedded systems often reside in machines that are expected to run continuously for years without errors, and in some cases recover by themselves if an error occurs. Therefore, the software is usually developed and tested more carefully than that for personal computers, and unreliable mechanical moving parts such as disk drives, switches or buttons are avoided. A variety of techniques are used, sometimes in combination, to recover from errors—both software bugs such as memory leaks , and also soft errors in the hardware:.

For high volume systems such as portable music players or mobile phones , minimizing cost is usually the primary design consideration. For low-volume or prototype embedded systems, general purpose computers may be adapted by limiting the programs or by replacing the operating system with a real-time operating system. In this design, the software simply has a loop. The loop calls subroutines , each of which manages a part of the hardware or software. Hence it is called a simple control loop or control loop. Some embedded systems are predominantly controlled by interrupts. This means that tasks performed by the system are triggered by different kinds of events; an interrupt could be generated, for example, by a timer in a predefined frequency, or by a serial port controller receiving a byte.

These kinds of systems are used if event handlers need low latency, and the event handlers are short and simple. Usually, these kinds of systems run a simple task in a main loop also, but this task is not very sensitive to unexpected delays. Sometimes the interrupt handler will add longer tasks to a queue structure. Later, after the interrupt handler has finished, these tasks are executed by the main loop.

This method brings the system close to a multitasking kernel with discrete processes. A nonpreemptive multitasking system is very similar to the simple control loop scheme, except that the loop is hidden in an API.

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  5. The advantages and disadvantages are similar to that of the control loop, except that adding new software is easier, by simply writing a new task, or adding to the queue. In this type of system, a low-level piece of code switches between tasks or threads based on a timer connected to an interrupt. This is the level at which the system is generally considered to have an "operating system" kernel.

    Depending on how much functionality is required, it introduces more or less of the complexities of managing multiple tasks running conceptually in parallel. As any code can potentially damage the data of another task except in larger systems using an MMU programs must be carefully designed and tested, and access to shared data must be controlled by some synchronization strategy, such as message queues , semaphores or a non-blocking synchronization scheme.

    Because of these complexities, it is common for organizations to use a real-time operating system RTOS , allowing the application programmers to concentrate on device functionality rather than operating system services, at least for large systems; smaller systems often cannot afford the overhead associated with a generic real-time system, due to limitations regarding memory size, performance, or battery life. The choice that an RTOS is required brings in its own issues, however, as the selection must be done prior to starting to the application development process.

    This timing forces developers to choose the embedded operating system for their device based upon current requirements and so restricts future options to a large extent. These trends are leading to the uptake of embedded middleware in addition to a real-time operating system. A microkernel is a logical step up from a real-time OS. The usual arrangement is that the operating system kernel allocates memory and switches the CPU to different threads of execution.

    User mode processes implement major functions such as file systems, network interfaces, etc. In general, microkernels succeed when the task switching and intertask communication is fast and fail when they are slow. Exokernels communicate efficiently by normal subroutine calls. The hardware and all the software in the system are available to and extensible by application programmers. In this case, a relatively large kernel with sophisticated capabilities is adapted to suit an embedded environment.

    This gives programmers an environment similar to a desktop operating system like Linux or Microsoft Windows , and is therefore very productive for development; on the downside, it requires considerably more hardware resources, is often more expensive, and, because of the complexity of these kernels, can be less predictable and reliable.

    Despite the increased cost in hardware, this type of embedded system is increasing in popularity, especially on the more powerful embedded devices such as wireless routers and GPS navigation systems. Here are some of the reasons:. In addition to the core operating system, many embedded systems have additional upper-layer software components. If the embedded device has audio and video capabilities, then the appropriate drivers and codecs will be present in the system. In the case of the monolithic kernels, many of these software layers are included. In the RTOS category, the availability of the additional software components depends upon the commercial offering.

    From Wikipedia, the free encyclopedia. Main article: Embedded software. Electronics portal. Neutrino Technical Library.

    go here Retrieved Embedded systems design. EDN series for design engineers 2 ed. An embedded system is a microprocessor based system that is built to control a function or a range of functions. Massa Programming embedded systems: with C and GNU development tools. Embedded Systems Design. TechInsights United Business Media. Electronic Frontier Foundation. Retrieved on Alippi: Intelligence for Embedded Systems. SenSys ' Electronic Engineering Journal. IPSN ' Prove it! Retrieved 2 February Computer sizes. Classes of computers. Ultra-mobile PC 2-in-1 Phablet Tabletop.

    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors
    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors
    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors
    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors
    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors
    Advanced Memory Optimization Techniques for Low Power Embedded Processors Advanced Memory Optimization Techniques for Low Power Embedded Processors

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