Efficient system-level functional verification methodology for multimedia applications

Multimedia application design exploration should begin at the system level, to meet low-power and minimum-area requirements. Existing validation techniques mainly concentrate on lower abstraction levels. This system-level methodology combines formal verification of loop-oriented transformations with correctness verification of arithmetic constructs and related control flows. A videoconferencing-decoder example illustrates the methodology's efficiency.     

Energy Aware Signal Processing for Software Defined Radio Baseband Implementation

The fast pacing diversity and evolution of wireless communications require a wide variety of baseband implementations within a short time-to-market. Besides, the exponentially increased design complexity and design cost of deep sub-micron silicon highly desire the designs to be reused as much as possible. This yields an increasing demand for reconfigurable/ programmable baseband solutions. Implementing all baseband functionalities on programmable architectures, as foreseen in the tier-2 SDR, will become necessary in the future. However, the energy efficiency of SDR baseband platforms is a major concern. This brings a challenging gap that is continuously broadened by the exploding baseband complexity. We advocate a system level approach to bridge the gap. Specifically, we fully leverage the advantages (programmability) of SDR platforms to compensate its disadvantages (energy efficiency). Highly flexible and dynamic baseband signal processing algorithms are designed and implemented to exploit the abundant dynamics in the environment and the user requirement. Instead of always performing the best effort, the baseband can dynamically and autonomously adjust its work load to optimize the average energy consumption. In this paper, we will introduce such baseband signal processing techniques optimized for SDR implementations. The methodology and design steps will be presented together with 3 representative case studies in HSDPA, WiMAX and 3GPP LTE.     

Formalized three-layer system-level model and reuse methodology forembedded data-dominated applications

In embedded data-dominated applications, a global system-level data transfer and storage exploration phase is crucial in obtaining a cost- and performance-efficient solution. We have developed a novel formalism to describe reusable blocks such that the essential part of the design exploration freedom is retained. This formalism is the basis for a system-level reuse methodology which allows reusing large parts of the design as heavily optimized structural VHDL or assembly code and describes the costly data access-related constructs at higher levels in the code hierarchy. Compared to a reuse approach based on fixed blocks, considerable power and area savings can be obtained, as demonstrated on real-life video and modem applications     

Power and Speed-Efficient Code Transformation of Video Compression Algorithms for RISC Processors

Upcoming multi-media compression applications will require high memory bandwidth. In this paper, we estimate that a software reference implementation of an MPEG-4 video decoder typically requires 200 Mtransfers/s to memory to decode 1 CIF (352×288) Video Object Plane (VOP) at 30 frames/s. This imposes a high penalty in terms of power but also performance.However, we also show that we can heavily improve on the memory transfers, without sacrificing speed (even gaining about 10% on cache misses and cycles for a DEC Alpha), by aggressive code transformations. For this purpose, we have manually applied an extended version of our data transfer and storage exploration (DTSE) methodology, which was originally developed for custom hardware implementations.     

Energy Aware Algorithm and Implementation of SDR Oriented HSDPA Chip Level Equalizer

The flexibility and programmability of SDR come at the expense of reduced efficiency and increased energy consumption. This is usually considered as the penalty of SDR. However, the flexibility and programmability have great potentials for improving the system-wide efficiency if they are properly exploited. In this paper, we present a HSDPA chip equalizer that is explicitly designed for SDR implementations. The first SDR-specific feature of our work is the multi-mode operation based on heterogeneous algorithms. The proposed equalizer combines an optimized LMS variant (with subspace-aware extension) and an optimized SRI-RLS algorithm based on QRD. Instead of always applying the powerful SRI-RLS algorithm, the equalizer switches to simple LMS-variant when possible. With negligible BER degradation, the multi-mode operation can reduce 60% of the cycle-count on TI TMS320C6713 for 3GPP case 4 with 16QAM modulation. The proposed equalizer framework also incorporates a generic, robust and efficient scheme for equalization-length adaptation. The length-adaptation scheme can make very fast run-time decision based on an efficient policy-template, which is optimized with large training set at design time. We test 14 representative channel profiles specified in ITU-R M.1225, 3GPP TR 25.943 and 3GPP TS 25.101. Comparing to worst-case based design the length-adaptation achieves more than 10× cycle-count reductions for ten of the cases.     

Address Generation Optimization for Embedded High-Performance Processors: A Survey

Nowadays embedded systems are growing at an impressive rate and provide more and more sophisticated applications characterized by having a complex array index manipulation and a large number of data accesses. Those applications require high performance specific computation that general purpose processors can not deliver at a reasonable energy consumption. Very long instruction word architectures seem a good solution providing enough computational performance at low power with the required programmability to speed up the time to market. Those architectures rely on compiler effort to exploit the available instruction and data parallelism to keep the data path busy all the time. With the density of transistors doubling each 18 months, more and more sophisticated architectures with a high number of computational resources running in parallel are emerging. With this increasing parallel computation, the access to data is becoming the main bottleneck that limits the available parallelism. To alleviate this problem, in current embedded architectures, a special unit works in parallel with the main computing elements to ensure efficient feed and storage of the data: the address generator unit, which comes in many flavors. Future architectures will have to deal with enormous memory bandwidth in distributed memories and the development of address generators units will be crucial for effective next generation of embedded processors where global trade-offs between reaction-time, bandwidth, energy and area must be achieved. This paper provides a survey of methods and techniques that optimize the address generation process for embedded systems, explaining current research trends and needs for future.

Experience with Widening Based Equivalence Checking in Realistic Multimedia Systems

The application of loop and data transformations to array and loop intensive programs is crucial to obtain a good performance. Designers often apply these transformations manually or semi-automatically. For the class of static affine programs, automatic methods exist for proving the correctness of these transformations. Realistic multimedia systems, however, often contain constructs that fall outside of this class. We present an extension of a widening based approach to handle the most relevant of these constructs, viz. accesses to array slices, data dependent accesses and data dependent assignments, and report on some experiments with non-trivial applications.     

Background memory area estimation for multidimensional signalprocessing systems

Memory cost is responsible for a large amount of the chip and/or board area of customized video and image processing system realizations. In this paper, we present a novel technique-founded on data-flow analysis which allows one to address the problem of background memory size evaluation for a given nonprocedural algorithm specification, operating on multidimensional signals with affine indexes. Most of the target applications are characterized by a huge number of signals, so a new polyhedral data-flow model operating on groups of scalar signals is proposed. These groups are obtained by a novel analytical partitioning technique, allowing to select a desired granularity, depending on the application complexity. The method incorporates a way to tradeoff memory size with computational and controller complexity     

Matisse: A System-on-Chip Design Methodology Emphasizing Dynamic Memory Management

MATISSE is a design environment intended for developing systems characterized by a tight interaction between control and data-flow behavior, intensive data storage and transfer, and stringent real-time requirements. Matisse bridges the gap from a system specification, using a concurrent object-oriented language, to an optimized embedded single-chip hardware/software implementation. Matisse supports stepwise exploration and refinement of dynamic memory management, memory architecture exploration, and gradual incorporation of timing constraints before going to traditional tools for hardware synthesis, software compilation, and inter-processor communication synthesis. With this approach, specifications of embedded systems can be written in a high-level programming language using data abstraction. Application of MATISSE on telecom protocol processing systems in the ATM area shows significant improvements in area usage and power consumption.