外文翻译--一个以 “ DSP算法和ASIC架构”为导向的硕士课程.docx

附录AA PROJECT-ORIENTED MASTER PROGRAMME INDSP ALGORITHMS AND ASIC ARCHITECTURESOver the last decade Digital Signal Processing (DSP) has evolved from being a term known by only a few specialists, to a household term. The growth in DSP applied in e.g., consumer, medical, communications, networking and computing devices has been spectacular. In fact, the digital signal processor market has grown 40% per year since 1988 and this figure is expected to continue over the next 10 years. At the same time the extreme improvement in hardware technologies has been paving the way for designing dedicated architectures for real time execution of still more complex DSP algorithms, continuously decreasing the power and silicon consumption required to perform certain functionalities. Consequently, we consider advanced DSP topics as being essential in the curriculum for a still growing number of electrical engineering students. These topics are basically related to 1) the design of highly complex DSP algorithms according to given specifications, and 2) real time implementation of these algorithms using various and conceptually different hardware architectures. Aalborg University, which has a long standing tradition for project-oriented teaching in traditional DSP theory at the Master level, therefore in 1994 launched a new Master programme in DSP Algorithms and ASIC Architectures. Now, after five years of very successful execution of this programme, we in this paper would like to report on our experiences.1. INTRODUCTIONThe evolution over the past 2-3 decades within the Digital Signal Processing community towards more sophisticated and complex algorithms has been the primary reason for the design of todays very powerful, flexible, and easy-to-use general purpose (GP) programmable Digital Signal Processor. In numerous application areas these devices exhibit an efficient trade-off between performance, required time for HW/SW design, and price. From the early 80s, Aalborg University therefore has offered a Master programme in traditional DSP design, i.e., application studies, algorithmic design and real time implementation onto GP DSP processors.In recent years, however, the number of applications which need support for high integration has increased substantially. In particular, portable systems, e.g., mobile communication systems and hearing aids (industrially represented by numbers in Denmark) are applications where extreme performance in terms of high speed, small physical size, low power consumption, and time to market is vital.For such types of applications, the GP programmable DSP is in many cases either lacking the ability to meet the specifications, or is simply an overkill.Consequently, in order to change our DSP Master candidate profile towards these new challenges, we started in1993 to look for alternative architectural possibilities, e.g.,1. With the state-of-the-art IC technology and ASIC design tools, we found that a very promising educational approach is to provide the students with an in-depth knowledge of the theories, methods and tools required in order to design and implement Application Specific Digital Signal Processors, fixed or programmable. Basically, these processors are stripped and customized versions of GP DSPs. Therefore, fundamental characteristics are 1) tailor-made instruction sets and 2) architectural topologies consisting of execution units tuned to the given application (i.e., set of algorithms). Essential subjects included in the Master programme is therefore advanced DSP theory, concepts for real time architectures and theories for optimizing the algorithmic and architectural interaction.After five years of continuous refinement, our Master programme is now running very successfully with 15-20 new Masters every year. In order to share our experiences, we in this paper will discuss 1) the overall organization of the project-oriented education strategy at Aalborg University, 2) the main objective and content of our Master programme, 3) a typical student project trajectory, and 4) general experiences.2. THE PROJECT-ORIENTED STRATEGYEstablished in 1974, Aalborg University now has employed a project-organized study strategy for almost 25 year, 2. The curriculum in engineering is project-organized from the day the freshmen arrive and until they graduate | the first year (i.e., two semesters) being spend learning how to do scientific work in project groups (typically 4-6 students, the exception being the Master project with normally 2 students). The next one and a half year in the undergraduate programmes, the project-work is mainly design-oriented. In contrast, the last two and a half years in the graduate programmes, the project-work is problem-oriented. Adding up, the Master degree is obtained after five years.In the design-oriented project-work, the students deal with know-how problems which can be solved by theories and knowledge they have acquired in their lectures. On the other hand, in the problem-oriented project-work, the students consider unsolved scientific problems. The project-work has a know-why approach and is supported by relevant lectures. The duration of each project is one semester, where half of the time is devoted to the project-work, 25%is spend on courses related to the projects and 25% is used for courses related to the curriculum.3. THE MASTER PROGRAMMEEntering the graduate level (the 6th semester being the entry), the students who want to obtain the Master degree in DSP Algorithms and ASIC Architectures are strongly encouraged to choose the Signal Processing direction (several options are available). In three semesters, the students will work with Deterministic Signal Processing, Stochastic Signal Processing, and Adaptive Signal Processing,respectively.Now, the main purpose of the Master programme (the two final semesters) is to provide the students with skills in analysis, design and implementation of real time DSP systems characterized by a high algorithmic and architectural complexity. The Master programme focuses on theories, methods and tools required for design, implementation and optimization of modern DSP systems, including the following items; _ design and/or analysis of complex DSP functionalities using high level languages, e.g., C, C+, or MatLab. The kind of functionalities investigated typically belong to the following categories;- extract information from an observed signal- eliminate/reduce unwanted signal components- fast and reliable signal transmission/detectionanalyze, modify and benchmark DSP algorithms in order to _t them optimally into a fixed or programmable target architecture. The curriculum therefore include;- definition of various cost functions- algorithmic graph representation- graph partitioning methods- analysis of inherent parallelism- single- and multi-processor scheduling- algorithmic transformations- numerical analysis, fixed and floating point analyze, design and implement dedicated prototype architectures for real time execution of the algorithm(s).The curriculum therefore include;- various arithmetics and execution units (EXU)- data- and control path topologies- instruction set and decoding principles- configuration of multiprocessor systems- communication in multiprocessor systems- heterogeneous and reconfigurable DSP systems- HW/SW co-design, and -verification- VHDL programming, simulation and synthesis- FPGA technologies and design tools4. A TYPICAL PROJECT TRAJECTORYThe design of a dedicated real time DSP system is initiated at the application level, i.e., first the students have to understand and describe the problem. This first step is trivial (the students have done this exercise several times before) but it provides valuable information for the next task where the class of algorithms typically employed within the given application have to be identified and analyzed. A detailed analysis of the algorithms is essential in order to select for example the appropriate data word length (signal-to-noise ratio and numerical stability). Beside, the computational characteristics of the algorithms have to be found. In particular, the students have to analyze 1) the types of operations found in the algorithms, 2) the overall computational complexity, 3) the types of data structures used by the algorithms, 4) the various memory access patterns, and 5) the variables life-times. Next, an appropriate assignment and allocation of 1) EXUs, 2) data address generators (DAG),3) memory type, -size and -organization, 4) communication hardware, and 5) I/O facilities is performed.Once the overall architectural structure has been decided upon, a refinement process is initiated where the students in detail design the data path. In some projects, the data path is designed using only standard EXUs like ALUs, MACs (Multiply ACcumulate), busses, and registers, but in others it also incorporate more algorithmic specific units, e.g., DIV, CORDIC, ABS, Sinus Look-Up-Table, dedicated Barrel-Shifter, and/or Bit-manipulation units. Finally, the controller is designed. It may be implemented as a simple FSM, or alternatively as a sophisticated sequencer supporting e.g., data dependent branching, nested loops, interrupts and subroutine constructs. So far, only the type of operations to be executed in the architecture has been known. The next step in the design trajectory is therefore to convert these operations into the actual instruction set in case a programmable architecture is required. Our experiences show that the instruction set design procedure in most student projects is very time consuming. This is basically due to the fact that many design iterations typically are needed before a reasonable match between the initial class of algorithms and the smallest possible and most efficient instruction set is found. In order to handle systematically these and the following steps in the design trajectory (i.e., the actual implementation), a set of commercial design tools are needed. For the architectural design, simulation, synthesis and prototyping, we have opted for VHDL and Alteras FLEX-series of FPGA. A small but efficient evaluation board, based on the FLEX 10K50 Altera FPGA connected to an UART for PC- interfacing and dual SRAM providing data- and programmemory, is available for each project group.5. GENERAL EXPERIENCESApart from minor modifications and updates, the Master programme is now running into its 6th year. Although the programme is quite intensive we found that it actually is possible during a two semester course to enable students to design operational FPGA prototype systems for complex DSP applications. The prerequisitions are a detailed knowledge of DSP theory and general digital circuit design. We are convinced that our success is due to the project-oriented education strategy. Working together in small groups, the students are highly motivated and prepared to spend some extra hours every day in order to achieve their project goals. Up til now, a variety of diffierent Master theses have been conducted, examples are available from 3 | some, unfortunately, are written in Danish, meaning that the next goal is to give our students a more international flavor.附录B一个以 “ DSP算法和ASIC架构”为导向的硕士课程在过去十年中数字信号处理（DSP）已从一个只有少数专家认知的术语，演变为一个家喻户晓的名词。DSP在应用方面的发展，例如，消费，医疗，通讯，网络和计算设备方面已经有了显著地成就。事实上，自1988年以来，数字信号处理器的销售额以每年40 增长 ，预计在未来10年将继续保持这样的增长。在同一时间，硬件技术极速发展已为实时执行的专用体系结构的设计铺平了道路，使DSP能完成更复杂的算法，不断降低功耗和成本，以便执行特定功能。因此，我们认为，先进的DSP的课题，仍将是许多电气工程系学生必不可少的课程。这些课题基本上是有关：根据给定的规格设计高度复杂的DSP算法；利用各种和概念上不同的硬体架构实时执行这些算法。奥尔堡大学在硕士水平上有关DSP的理论课题的教学有着悠久历史传统，并且，在1994年推出了一项新的硕士课程，在“ DSP算法和ASIC架构” 。现在，我们在这想对我们这5年来这一方案的成功执行做出我们的经验报告。 1导言在过去的二、三十年内的数字信号处理一直朝向更精密和复杂的算法演变的最主要的原因是今天设计的非常强大，灵活和易于使用的通用（GP ）的可编程数字信号处理器。在众多的应用领域，这些设备展示一个性价比，所需的时间，软/硬体设计，和价格都很好。从80年代初，奥尔堡大学提供了传统的DSP设计硕士课程，即在DSP处理器上执行GP算法设计和实时性的应用研究， 然而，近年来，申请数目其中需要支持高集成度已大幅增加。特别是，便携系统，例如移动通信系统和助听器（在丹麦代表工业化为的数字）是应用而极速发展的表现，高速，体形小，功耗低，消费市场大是vital.for等类型的应用程序， GP的可编程DSP在许多情况下，要么缺乏能力，以满足规格，或根本是矫枉过正。 因此，为了改变我们的DSP掌握候选人的个人资料对这些新的挑战，我们1993年开始寻找其他的可能性，例如， 1.与国家标准IC技术和ASIC设计工具，我们发现一个非常有前途的教育方法是提供学生一个在深入了解理论的同时，满足方法和工具的需要，以便设计和实施的应用具体的数字信号处理器，固定或可编程。基本上，这些处理器是被剥夺和定制版本的GP的DSP的。因此，基本特征是：量身定作指令集和；以给定的应用（即，一套算法）建拓扑结构构成的执行的单位调整。这一必不可少的科目包括在硕士学位课程种，因此，先进的DSP的理论，概念，实时性架构和理论的优化算法和建筑的互动。 经过五年的不断改进，我们的硕士课程，现在已近非常成功了。每年与15-20的新人以分享我们的经验，我们在这方面的文件将讨论：整体组织的面向项目的教育策略，在奥尔堡大学：研究工作的主要目的和内容，我们的硕士课程；一个典型的学生项目的轨迹；一般的经验。 2该项目导向战略成立于1974年，奥尔堡大学，现在已拥有一个项目，组织研究策略，几乎二十五年，该课程是在工程项目的组织从创建之日起新生的到来，直到他们毕业，第一年（即，两个学期）学习如何做科学工作的项目组（通常是4月6日的学生，除作为硕士项目，通常二学生）。在未来一年的一个半月中，本科课程的工作，主要是面向设计的。在此相反，过去两年半来，在研究生课程的工作是面向问题的。加入五年后，获得硕士学位，。 在面向项目的设计工作中，学生的掌握了处理问题的诀窍是可以解决的理论和知识，他们演讲已获得理论知识。在另一方面，在这个问题为导向的项目工作中，学生考虑解决的科学问题。项目工作有一个知道为什么态度和支持有关的讲座。每一个项目时间都是一个学期，其中一半的时间是用于该项目的工作， 25 是用对有关的课程项目和25 是用于课程相关的课程。 3硕士学位课程进入研究生水平（第六学期正在进入） ，谁的学生要取得“DSP算法和ASIC架构”硕士学位， ，我们鼓励选择“信号处理”的方向（几个可供选择） 。在3个学期，学生将以“确定性信号处理”，“随机信号处理” ，和“自适应信号处理” 进行分别。 现在，硕士学位课程（最后两学期） 主要目的是提供学生分析技能，设计和实施的实时DSP系统的特点是高算法和建筑的复杂性。主方案的重点是理论，方法和工具所需的设计，执行和优化现代DSP系统，包括下列项目：_设计或分析复杂