1,556 research outputs found

    Baseband analog front-end and digital back-end for reconfigurable multi-standard terminals

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    Multimedia applications are driving wireless network operators to add high-speed data services such as Edge (E-GPRS), WCDMA (UMTS) and WLAN (IEEE 802.11a,b,g) to the existing GSM network. This creates the need for multi-mode cellular handsets that support a wide range of communication standards, each with a different RF frequency, signal bandwidth, modulation scheme etc. This in turn generates several design challenges for the analog and digital building blocks of the physical layer. In addition to the above-mentioned protocols, mobile devices often include Bluetooth, GPS, FM-radio and TV services that can work concurrently with data and voice communication. Multi-mode, multi-band, and multi-standard mobile terminals must satisfy all these different requirements. Sharing and/or switching transceiver building blocks in these handsets is mandatory in order to extend battery life and/or reduce cost. Only adaptive circuits that are able to reconfigure themselves within the handover time can meet the design requirements of a single receiver or transmitter covering all the different standards while ensuring seamless inter-interoperability. This paper presents analog and digital base-band circuits that are able to support GSM (with Edge), WCDMA (UMTS), WLAN and Bluetooth using reconfigurable building blocks. The blocks can trade off power consumption for performance on the fly, depending on the standard to be supported and the required QoS (Quality of Service) leve

    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

    Enhancing an Embedded Processor Core with a Cryptographic Unit for Performance and Security

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    We present a set of low-cost architectural enhancements to accelerate the execution of certain arithmetic operations common in cryptographic applications on an extensible embedded processor core. The proposed enhancements are generic in the sense that they can be beneficially applied in almost any RISC processor. We implemented the enhancements in form of a cryptographic unit (CU) that offers the programmer an extended instruction set. The CU features a 128-bit wide register file and datapath, which enables it to process 128-bit words and perform 128-bit loads/stores. We analyze the speed-up factors for some arithmetic operations and public-key cryptographic algorithms obtained through these enhancements. In addition, we evaluate the hardware overhead (i.e. silicon area) of integrating the CU into an embedded RISC processor. Our experimental results show that the proposed architectural enhancements allow for a significant performance gain for both RSA and ECC at the expense of an acceptable increase in silicon area. We also demonstrate that the proposed enhancements facilitate the protection of cryptographic algorithms against certain types of side-channel attacks and present an AES implementation hardened against cache-based attacks as a case study

    Dataflow Computing with Polymorphic Registers

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    Heterogeneous systems are becoming increasingly popular for data processing. They improve performance of simple kernels applied to large amounts of data. However, sequential data loads may have negative impact. Data parallel solutions such as Polymorphic Register Files (PRFs) can potentially accelerate applications by facilitating high speed, parallel access to performance-critical data. Furthermore, by PRF customization, specific data path features are exposed to the programmer in a very convenient way. PRFs allow additional control over the registers dimensions, and the number of elements which can be simultaneously accessed by computational units. This paper shows how PRFs can be integrated in dataflow computational platforms. In particular, starting from an annotated source code, we present a compiler-based methodology that automatically generates the customized PRFs and the enhanced computational kernels that efficiently exploit them

    06141 Abstracts Collection -- Dynamically Reconfigurable Architectures

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    From 02.04.06 to 07.04.06, the Dagstuhl Seminar 06141 ``Dynamically Reconfigurable Architectures\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    Performance and area evaluations of processor-based benchmarks on FPGA devices

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    The computing system on SoCs is being long-term research since the FPGA technology has emerged due to its personality of re-programmable fabric, reconfigurable computing, and fast development time to market. During the last decade, uni-processor in a SoC is no longer to deal with the high growing market for complex applications such as Mobile Phones audio and video encoding, image and network processing. Due to the number of transistors on a silicon wafer is increasing, the recent FPGAs or embedded systems are advancing toward multi-processor-based design to meet tremendous performance and benefit this kind of systems are possible. Therefore, is an upcoming age of the MPSoC. In addition, most of the embedded processors are soft-cores, because they are flexible and reconfigurable for specific software functions and easy to build homogenous multi-processor systems for parallel programming. Moreover, behavioural synthesis tools are becoming a lot more powerful and enable to create datapath of logic units from high-level algorithms such as C to HDL and available for partitioning a HW/SW concurrent methodology. A range of embedded processors is able to implement on a FPGA-based prototyping to integrate the CPUs on a programmable device. This research is, firstly represent different types of computer architectures in modern embedded processors that are followed in different type of software applications (eg. Multi-threading Operations or Complex Functions) on FPGA-based SoCs; and secondly investigate their capability by executing a wide-range of multimedia software codes (Integer-algometric only) in different models of the processor-systems (uni-processor or multi-processor or Co-design), and finally compare those results in terms of the benchmarks and resource utilizations within FPGAs. All the examined programs were written in standard C and executed in a variety numbers of soft-core processors or hardware units to obtain the execution times. However, the number of processors and their customizable configuration or hardware datapath being generated are limited by a target FPGA resource, and designers need to understand the FPGA-based tradeoffs that have been considered - Speed versus Area. For this experimental purpose, I defined benchmarks into DLP / HLS catalogues, which are "data" and "function" intensive respectively. The programs of DLP will be executed in LEON3 MP and LE1 CMP multi-processor systems and the programs of HLS in the LegUp Co-design system on target FPGAs. In preliminary, the performance of the soft-core processors will be examined by executing all the benchmarks. The whole story of this thesis work centres on the issue of the execute times or the speed-up and area breakdown on FPGA devices in terms of different programs

    Memory Hierarchy Hardware-Software Co-design in Embedded Systems

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    The memory hierarchy is the main bottleneck in modern computer systems as the gap between the speed of the processor and the memory continues to grow larger. The situation in embedded systems is even worse. The memory hierarchy consumes a large amount of chip area and energy, which are precious resources in embedded systems. Moreover, embedded systems have multiple design objectives such as performance, energy consumption, and area, etc. Customizing the memory hierarchy for specific applications is a very important way to take full advantage of limited resources to maximize the performance. However, the traditional custom memory hierarchy design methodologies are phase-ordered. They separate the application optimization from the memory hierarchy architecture design, which tend to result in local-optimal solutions. In traditional Hardware-Software co-design methodologies, much of the work has focused on utilizing reconfigurable logic to partition the computation. However, utilizing reconfigurable logic to perform the memory hierarchy design is seldom addressed. In this paper, we propose a new framework for designing memory hierarchy for embedded systems. The framework will take advantage of the flexible reconfigurable logic to customize the memory hierarchy for specific applications. It combines the application optimization and memory hierarchy design together to obtain a global-optimal solution. Using the framework, we performed a case study to design a new software-controlled instruction memory that showed promising potential.Singapore-MIT Alliance (SMA

    An FPGA Implementation of HW/SW Codesign Architecture for H.263 Video Coding

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    Chapitre 12 http://www.intechopen.com/download/pdf/pdfs_id/1574

    Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy

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    Deep Neural Networks (DNNs) are known to be strong predictors, but their prediction strategies can rarely be understood. With recent advances in Explainable Artificial Intelligence, approaches are available to explore the reasoning behind those complex models' predictions. One class of approaches are post-hoc attribution methods, among which Layer-wise Relevance Propagation (LRP) shows high performance. However, the attempt at understanding a DNN's reasoning often stops at the attributions obtained for individual samples in input space, leaving the potential for deeper quantitative analyses untouched. As a manual analysis without the right tools is often unnecessarily labor intensive, we introduce three software packages targeted at scientists to explore model reasoning using attribution approaches and beyond: (1) Zennit - a highly customizable and intuitive attribution framework implementing LRP and related approaches in PyTorch, (2) CoRelAy - a framework to easily and quickly construct quantitative analysis pipelines for dataset-wide analyses of explanations, and (3) ViRelAy - a web-application to interactively explore data, attributions, and analysis results.Comment: 10 pages, 3 figure
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