500 research outputs found

    Coarse-grained reconfigurable array architectures

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    Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

    Task scheduling and placement for reconfigurable devices

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    Partially reconfigurable devices allow the execution of different tasks at the same time, removing tasks when they finish and inserting new tasks when they arrive. This dissertation investigates scheduling and placing real-time tasks (tasks with deadline) on reconfigurable devices. One basic scheduler is the First-Fit scheduler. By allowing the First-Fit scheduler to retry tasks while they can satisfy their deadlines, we found that its performance can be enhanced to be better than other schedulers. We also proposed a placement idea based on partitioning the reconfigurable area into regions of various widths, assigning a task to a region based on its width. This idea has a similar rejection rate to a First-Fit scheduler that retries placing tasks and performs better than the First-Fit that does not retry tasks. Also, this regions-based scheduling method has a better running time. Managing how the space will be shared among tasks is a problems of interest. The main function of the free-space manager is to maintain information about the free space (areas not used by active tasks) after any placement or deletion of a task. Speed and efficiency of the free-space data structure are important as well as its effect on scheduler performance. We introduce the use of maximal horizontal strips and maximal vertical strips to represent free space. This resulted in a faster free space manager compared to what has been used in the area. Most researchers in the area of scheduling on reconfigurable devices assumed a homogeneous FPGA with only CLBs in the reconfigurable area. Most reconfigurable devices offered in the market, however, are not homogeneous but heterogeneous with other components between CLBs. We studied the effect of heterogeneity on the performance of schedulers designed for a homogeneous structure. We found that current schedulers result in worse performance when applied to a heterogeneous structure, but by simple modifications, we can apply them to a heterogeneous structure and achieve good performance. Consequently, the approach of studying homogeneous FPGAs is a valid one, as the scheduling ideas discovered there do carry over to heterogeneous FPGAs

    Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence

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    This paper describes a novel way to exploit the computation capabilities delivered by modern Field-Programmable Gate Arrays (FPGAs), not only towards a higher performance, but also towards an improved reliability. Computation-specific pieces of circuitry are dynamically scheduled and allocated to different resources on the chip based on a set of novel algorithms which are described in detail in this article. These algorithms consider most of the technological constraints existing in modern partially reconfigurable FPGAs as well as spontaneously occurring faults and emerging permanent damage in the silicon substrate of the chip. In addition, the algorithms target other important aspects such as communications and synchronization among the different computations that are carried out, either concurrently or at different times. The effectiveness of the proposed algorithms is tested by means of a wide range of synthetic simulations, and, notably, a proof-of-concept implementation of them using real FPGA hardware is outlined

    Efficient Algorithms for Online Task Placement on Runtime Partially Reconfigurable FPGA

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    Recent generations of FPGAs allow run-time partial reconfiguration. One of the challenging problems in such a multitasking systems is online placement of task. Many online task placement algorithms designed for such partially reconfigurable systems have been proposed to provide efficient and fast task placement. In this paper two different approaches are being used to place the incoming tasks. The first method is uses a run-length based representation that defines the vacant slots on the FPGA. This compact representation allows the algorithm to locate a vacant area suitable to accommodate the incoming task quickly. In the proposed FPGA model, the CLBs are numbered according to Peano Space filling curve model. The second approach is based on harmonic packing. Simulation experiments indicate that proposed techniques result in low ratio of task rejection compared to existing techniques

    Resource-efficient dynamic partial reconfiguration on FPGAs for space instruments

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    Field-Programmable Gate Arrays (FPGAs) provide highly flexible platforms to implement sophisticated data processing for scientific space instruments. The dynamic partial reconfiguration (DPR) capability of FPGAs allows it to schedule HW tasks. While this feature adds another dimension of processing power that can be exploited without significantly increasing system complexity and power consumption, there are still several challenges for an efficient DPR use. State-of-the-art concepts concentrate either on resource-efficient implementations at design time or flexible HW task scheduling at runtime. In this paper we propose a balanced algorithm that considers both optimization goals and is well suited for resource-limited space applications

    Design of an Adaptable Run-Time Reconfigurable Software-Defined Radio Processing Architecture

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    Processing power is a key technical challenge holding back the development of a high-performance software defined radio (SDR). Traditionally, SDR has utilized digital signal processors (DSPs), but increasingly complex algorithms, higher data rates, and multi-tasking needs have exceed the processing capabilities of modern DSPs. Reconfigurable computers, such as field-programmable gate arrays (FPGAs), are popular alternatives because of their performance gains over software for streaming data applications like SDR. However, FPGAs have not yet realized the ideal SDR because architectures have not fully utilized their partial reconfiguration (PR) capabilities to bring needed flexibility. A reconfigurable processor architecture is proposed that utilizes PR in reconfigurable computers to achieve a more sophisticated SDR. The proposed processor contains run-time swappable blocks whose parameters and interconnects are programmable. The architecture is analyzed for performance and flexibility and compared with available alternate technologies. For a sample QPSK algorithm, hardware performance gains of at least 44x are seen over modern desktop processors and DSPs while most of their flexibility and extensibility is maintained
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