José M. Mendías

A Complete Network-On-Chip Emulation Framework

Current systems-on-chip (SoC) execute applications that demand extensive parallel processing. Networks-on-chip (NoC) provide a structured way of realizing interconnections on silicon, and obviate the limitations of bus-based solutions. NoC can have regular or ad hoc topologies, and functional validation is essential to assess their correctness and performance. In this paper, we present a flexible emulation environment implemented on an FPGA that is suitable to explore, evaluate and compare a wide range of NoC solutions with a very limited effort. Our experimental results show a speed-up of four orders of magnitude with respect to cycle-accurate HDL simulation, while retaining cycle accuracy. With our emulation framework, designers can explore and optimize a various range of solutions, as well as characterize quickly performance figures.

An integrated hardware/software approach for run-time scratchpad management

An ever increasing number of dynamic interactive applications are implemented on portable consumer electronics. Designers depend largely on operating systems to map these applications on the architecture. However, todays embedded operating systems abstract away the precise architectural details of the platform. As a consequence, they cannot exploit the energy efficiency of scratchpad memories. We present in this paper a novel integrated hardware/software solution to support scratchpad memories at a high abstraction level. We exploit hardware support to alleviate the transfer cost from/to the scratchpad memory and at the same time provide a high-level programming interface for run-time scratchpad management. We demonstrate the effectiveness of our approach with a case-study.

A fast HW/SW FPGA-based thermal emulation framework for multi-processor system-on-chip

With the growing complexity in consumer embedded products and the improvements in process technology, multi-processor system-on-chip (MPSoC) architectures have become widespread. These new systems are complex to design as they must execute multiple complex applications (e.g. video processing, 3D games), while meeting additional design constraints (e.g. energy consumption or time-to-market). Moreover, the rise of temperature in the die for MPSoC components can seriously affect their final performance and reliability. Therefore, mechanisms to efficiently evaluate complete HW/SW MPSoC designs in terms of energy consumption, temperature, performance and other key metrics are needed. In this paper, we present a new HW/SW FPGA-based emulation framework that allows designers to rapidly extract a number of critical statistics from processing cores, memories and interconnection systems being emulated on a FPGA. This information is then used to interact in real-time with a SW thermal model running on a host computer via an Ethernet port. The results show speed-ups of three orders of magnitude compared to cycle-accurate MPSoC simulators, which enable a very fast exploration of a large range of MPSoC design alternatives at the cycle-accurate level. Finally, our HW/SW framework allows designers to test run-time thermal management strategies with real-life inputs without any loss in the performance of the emulated system

HW-SW emulation framework for temperature-aware design in MPSoCs

New tendencies envisage multiprocessor systems-on-chips (MPSoCs) as a promising solution for the consumer electronics market. MPSoCs are complex to design, as they must execute multiple applications (games, video) while meeting additional design constraints (energy consumption, time-to-market). Moreover, the rise of temperature in the die for MPSoCs can seriously affect their final performance and reliability. In this article, we present a new hardware-software emulation framework that allows designers a complete exploration of the thermal behavior of final MPSoC designs early in the design flow. The proposed framework uses FPGA emulation as the key element to model hardware components of the considered MPSoC platform at multimegahertz speeds. It automatically extracts detailed system statistics that are used as input to our software thermal library running in a host computer. This library calculates at runtime the temperature of on-chip components, based on the collected statistics from the emulated system and final floorplan of the MPSoC. This enables fast testing of various thermal management techniques. Our results show speedups of three orders of magnitude compared to cycle-accurate MPSoC simulators.

Systematic dynamic memory management design methodology for reduced memory footprint

New portable consumer embedded devices must execute multimedia and wireless network applications that demand extensive memory footprint. Moreover, they must heavily rely on Dynamic Memory (DM) due to the unpredictability of the input data (e.g., 3D streams features) and system behavior (e.g., number of applications running concurrently defined by the user). Within this context, consistent design methodologies that can tackle efficiently the complex DM behavior of these multimedia and network applications are in great need. In this article, we present a new methodology that allows to design custom DM management mechanisms with a reduced memory footprint for such kind of dynamic applications. First, our methodology describes the large design space of DM management decisions for multimedia and wireless network applications. Then, we propose a suitable way to traverse the aforementioned design space and construct custom DM managers that minimize the DM used by these highly dynamic applications. As a result, our methodology achieves improvements of memory footprint by 60% on average in real case studies over the current state-of-the-art DM managers used for these types of dynamic applications.

A novel approach for network on chip emulation

Current systems-on-chip execute applications that demand extensive parallel processing. Networks-on-chip (NoC) provide a structured way of realizing interconnections on silicon, and obviate the limitations of bus-based solutions. NoCs can have regular or ad hoc topologies, and functional validation is essential to assess their correctness and performance. In this paper, we present a flexible emulation environment implemented on an FPGA that is suitable to explore, evaluate and compare a wide range of NoC solutions with a very limited effort. Our experimental results show a speed-up of four orders of magnitude with respect to cycle-accurate HDL simulation, while retaining cycle accuracy. With our emulation framework, designers can explore and optimize a range of solutions, as well as characterize quickly performance figures.

Memory-access-aware data structure transformations for embedded software with dynamic data accesses

Embedded systems are evolving from traditional, stand-alone devices to devices that participate in Internet activity. The days of simple, manifest embedded software [e.g. a simple finite-impulse response (FIR) algorithm on a digital signal processor (DSP] are over. Complex, nonmanifest code, executed on a variety of embedded platforms in a distributed manner, characterizes next generation embedded software. One dominant niche, which we concentrate on, is embedded, multimedia software. The need is present to map large scale, dynamic, multimedia software onto an embedded system in a systematic and highly optimized manner. The objective of this paper is to introduce high-level, systematically applicable, data structure transformations and to show in detail the practical feasibility of our optimizations on three real-life multimedia case studies. We derive Pareto tradeoff points in terms of accesses versus memory footprint and obtain significant gains in execution time and power consumption with respect to the initial implementation choices. Our approach is a first step to systematically applying high-level data structure transformations in the context of memory-efficient and low-power multimedia systems.

Multi-processor operating system emulation framework with thermal feedback for systems-on-chip

Multi-Processor System-On-Chip (MPSoC) can provide the performance levels required by high-end embedded applications. However, they do so at the price of an increasing power density, which may lead to thermal runaway if coupled with low-cost packaging and cooling. Hence, mechanisms to efficiently evaluate the effectiveness of advanced thermal-aware operating-system (OS) strategies (e.g. task migration) onto the available MPSoC hardware are needed. In this paper, we propose a new MPSoC OS emulation framework that enables the study of thermal management strategies at the architectural- and OS-levels with the help of a standard FPGA. This framework includes the hardware and software components needed to accurately model complex MPSoCs architectures, and to test the effects of run-time thermal management strategies at the OS/middleware level with real-life inputs. Our results show that migration overhead is negligible w.r.t. temperature timings, enabling the development of thermal-aware migration strategies. Moreover, the effectiveness of the monitoring and feedback mechanism provides an emulation performance only ten times slower than real time.

Bitwise scheduling to balance the computational cost of behavioral specifications

Conventional scheduling algorithms try to balance the number of operations of every different type executed per cycle. However, in most cases, a uniform distribution is not reachable, and thus, some hardware (HW) waste appears. This situation becomes worse when heterogeneous specifications (those formed by operations with different data formats and widths) are synthesized. Our proposal is an innovative bit-level algorithm able to minimize this HW waste. In order to obtain uniform distributions of the computational cost of operations among cycles, it successively transforms specification operations into sets of smaller ones, which are then scheduled independently. As a consequence, some specification operations may be executed during a set of nonconsecutive cycles, and over several functional units. In combination with allocation algorithms able to guarantee the bit-level reuse of HW resources, our approach produces circuits with substantially smaller area than conventional implementations. Due to the fragmentation of operations, in the proposed implementations, the type, number, and width of HW resources are, in general, independent of the type, number, and width of both specification operations and variables. Additionally, the clock-cycle length is also reduced in most circuits.

A Distributed Controller for Managing Speculative Functional Units in High Level Synthesis

Speculative functional units (SFUs) are arithmetic functional units that operate using a predictor for the carry signal. The carry prediction helps to shorten the critical path of the functional unit. The average case performance of these units is determined by the hit rate of the prediction. In case of mispredictions, the SFUs need to be coordinated by the datapath control mechanism to perform corrections and to maintain the datapath in the correct state. Devising a control mechanism for correcting mispredictions without adversely impacting overall performance is the most important challenge. In this paper, we present techniques for designing a datapath controller for seamless deployment of SFUs in high level synthesis. We have developed two techniques based on two main control paradigms: centralized and distributed control. The centralized approach stops the execution of the entire datapath for each misprediction and resumes execution once the correct value of the carry is known. The distributed approach decouples the functional unit suffering from the misprediction from the rest of the datapath. Hence, it allows the remainder of the functional units to carry on execution and be at different scheduling states at different times. We tested datapaths utilizing both linear structures and logarithmic structures for speculative arithmetic functional units. Our results show that it is possible to reduce execution time by as much as 38% (33% on average) for linear structures and by as much as 37.2% (25% on average) for logarithmic structures.