Juanjo Noguera

High-Level Synthesis for FPGAs: From Prototyping to Deployment

Escalating system-on-chip design complexity is pushing the design community to raise the level of abstraction beyond register transfer level. Despite the unsuccessful adoptions of early generations of commercial high-level synthesis (HLS) systems, we believe that the tipping point for transitioning to HLS msystem-on-chip design complexityethodology is happening now, especially for field-programmable gate array (FPGA) designs. The latest generation of HLS tools has made significant progress in providing wide language coverage and robust compilation technology, platform-based modeling, advancement in core HLS algorithms, and a domain-specific approach. In this paper, we use AutoESLs AutoPilot HLS tool coupled with domain-specific system-level implementation platforms developed by Xilinx as an example to demonstrate the effectiveness of state-of-art C-to-FPGA synthesis solutions targeting multiple application domains. Complex industrial designs targeting Xilinx FPGAs are also presented as case studies, including comparison of HLS solutions versus optimized manual designs. In particular, the experiment on a sphere decoder shows that the HLS solution can achieve an 11-31% reduction in FPGA resource usage with improved design productivity compared to hand-coded design.

Iris: an architecture for cognitive radio networking testbeds

Iris is a software architecture for building highly reconfigurable radio networks. It has formed the basis for a wide range of dynamic spectrum access and cognitive radio demonstration systems presented at a number of international conferences between 2007 and 2010. These systems have been developed using heterogeneous processing platforms including general-purpose processors, field-programmable gate arrays and the Cell Broadband Engine. Focusing on runtime reconfiguration, Iris offers support for all layers of the network stack and provides a platform for the development of not only reconfigurable point-to-point radio links but complete networks of cognitive radios. This article provides an overview of Iris, presenting the unique features of the architecture and illustrating how it can be used to develop a cognitive radio testbed.

Multitasking on reconfigurable architectures: microarchitecture support and dynamic scheduling

Dynamic scheduling for system-on-chip (SoC) platforms has become an important field of research due to the emerging range of applications with dynamic behavior (e.g., MPEG-4). Dynamically reconfigurable architectures are an interesting solution for this type of applications. Scheduling for dynamically reconfigurable architectures might be classified in two major broad categories: (1) static scheduling techniques or (2) use of an operating system (OS) for reconfigurable computing. However, research efforts demonstrate a trend to move tasks traditionally assigned to the OS into hardware (thus increasing performance and reducing power).In this paper, we introduce a methodology for dynamically reconfigurable architectures. The dynamic scheduling of tasks to several reconfigurable units is performed by a hardware-based multitasking support unit. Two different versions of the microarchitecture are possible (with or without a hardware configuration prefetch unit). The dynamic scheduling algorithms are also explained. Both algorithms try to minimize the reconfiguration overhead by overlapping the execution of tasks with device reconfigurations.An exhaustive study (using the developed simulation and performance analysis framework) of this novel proposal is presented, and the effect of the microarchitecture parameters has been studied. Results demonstrate the benefits of our approach (achieving similar performance to a static configuration solution but using half of the resources). The hardware configuration prefetch unit is useful (i.e., minimize the execution time) in applications with low level of parallelism.

HW/SW codesign techniques for dynamically reconfigurable architectures

Hardware/software (HW/SW) codesign and reconfigurable computing are commonly used methodologies for digital-systems design. However, no previous work has been carried out in order to define a HW/SW codesign methodology with dynamic scheduling for run-time reconfigurable architectures. In addition, all previous approaches to reconfigurable computing multicontext scheduling are based on static-scheduling techniques. In this paper, we present three main contributions: 1) a novel HW/SW codesign methodology with dynamic scheduling for discrete event systems using dynamically reconfigurable architectures; 2) a new dynamic approach to reconfigurable computing multicontext scheduling; and 3) a HW/SW partitioning algorithm for dynamically reconfigurable architectures. We have developed a whole codesign framework, where we have applied our methodology and algorithms to the case study of software acceleration. An exhaustive study has been carried out, and the obtained results demonstrate the benefits of our approach.

Fast dynamic and partial reconfiguration data path with low hardware overhead on Xilinx FPGAs

Dynamic and partial reconfiguration of Xilinx FPGAs is a well known technique in runtime adaptive system design. With this technique, parts of a configuration can be substituted while other parts stay operative without any disturbance. The advantage is the fact, that the spatial and temporal partitioning can be exploited with the goal to increase performance and to reduce power consumption due to the re-use of chip area. This paper shows a novel methodology for the inclusion of the configuration access port into the data path of a processor core in order to adapt the internal architecture and to re-use this access port as data- sink and source. It is obvious that the chip area, which is utilized by the hardware drivers for the internal configuration access port (ICAP), has to be as small as possible in comparison to the application functionality. Therefore, a hardware design with a small footprint, but with an adequate performance in terms of data throughput, is necessary. This paper presents a fast data path for dynamic and partial reconfiguration data with the advantage of a small footprint on the hardware resources.

Power Reduction in Network Equipment Through Adaptive Partial Reconfiguration

We introduce a new approach to reducing FPGA power consumption. By exploiting the time varying nature of a systems environment, we are able to extract power consumption savings. We do this by closely tracking environmental changes and adapting the implementation accordingly using partial reconfiguration. We chose network infrastructure equipment to provide the context for the work since it is a significant consumer of FPGAs and is deployed in diverse environments. The network industry is also very interested in reducing FPGA power consumption as part of a major system wide effort, since it faces regulatory pressure, environmental concerns and rising electricity bills. We present a new experimental framework for measuring the power consumption of FPGA cores. The framework is used in an illustrative case study of how the approach works with a Viterbi decoder. The experiments give encouraging results and show that significant savings in power consumption can be obtained.

Dynamic run-time HW/SW scheduling techniques for reconfigurable architectures

Dynamic run-time scheduling in System-on-Chip platforms has become recently an active area of research because of the performance and power requirements of new applications. Moreover, dynamically reconfigurable logic (DRL) architectures are an exciting alternative for embedded systems design. However, all previous approaches to DRL multi-context scheduling and HW/SW scheduling for DRL architectures are based on static scheduling techniques. In this paper, we address this problem and present: (1) a dynamic scheduler hardware architecture, and (2) four dynamic run-time scheduling algorithms for DRL-based multi-context platforms. The scheduling algorithms have been integrated in our codesign environment, where a large number of experiments have been carried out. Results demonstrate the benefits of our approach.

A Model-Based Approach to Cognitive Radio Design

Cognitive radio is a promising technology for fulfilling the spectrum and service requirements of future wireless communication systems. Real experimentation is a key factor for driving research forward. However, the experimentation testbeds available today are cumbersome to use, require detailed platform knowledge, and often lack high level design methods and tools. In this paper we propose a novel cognitive radio design technique, based on a high-level model which is implementation independent, supports design-time correctness checks, and clearly defines the underlying execution semantics. A radio designed using this technique can be synthesised to various real radio platforms automatically; detailed knowledge of the target platform is not required. The proposed technique therefore simplifies cognitive radio design and implementation significantly, allowing researchers to validate ideas in experiments without extensive engineering effort. One example target platform is proposed, comprising software and reconfigurable hardware. The design technique is demonstrated for this platform through the development of two realistic cognitive radio applications.

System-level power-performance trade-offs in task scheduling for dynamically reconfigurable architectures

Dynamic scheduling for System-on-Chip (SoC) platforms has become an important field of research due to the emerging range of applications with dynamic behavior (e.g. MPEG-4). Dynamically reconfigurable architectures are an interesting solution for this type of applications.However, dynamic scheduling for run-time reconfigurable architectures with power-performance trade-offs has not been addressed in previous research efforts. In this paper, we address this open issue using a system-level approach. Within our approach, we have used clock-gating and frequency-scaling strategies for power consumption minimization, jointly with our proposed architecture and scheduling algorithms.Device reconfiguration is a high-power consumption process. Thus reducing the number of device reconfigurations not only helps to reduce the reconfiguration overhead penalty (minimizing the application execution time), but also helps to reduce the system-level power consumption. Thus, dynamic task scheduling and reconfiguration context scheduling become a critical issue for power-performance trade-offs in embedded systems design.

Generic Software Framework for Adaptive Applications on FPGAs

Adaptive systems are set to become more mainstream, as numerous practical applications in the communications domain emerge. FPGAs offer an ideal implementation platform, combining high performance with flexibility. While significant research has been undertaken in the area of FPGA partial reconfiguration, it has focussed primarily on low-level architecture-specific implementations. Building upon this previous work, we present a system model and software architecture for implementing runtime adaptive applications on FPGAs, separating the control and processing planes and abstracting away the details of hardware reconfiguration from the system designer. Hardware processing components appear as software components in the runtime system, enabling their inclusion in adaptive applications. We present an adaptive wireless application, demonstrating the use of the model and software architecture.