Heterogeneous Reconfigurable Systems Research Articles

Lightweight asynchronous scheduling in heterogeneous reconfigurable systems

The trend for heterogeneous embedded systems is the integration of accelerators and general-purpose CPU cores on the same die. In these integrated architectures, like the Zynq UltraScale+ board (CPU+FPGA) that we target in this work, hardware support for shared memory and low-overhead synchronization between the accelerator and the CPU cores make the case for exploring strategies that exploit a tight collaboration between the CPUs and the accelerator. In this paper we propose a novel lightweight scheduling strategy, FastFit, targeted to FPGA accelerators, and a new scheduler based on it, named MultiFastFit, which asynchronously tackles heterogeneous systems comprised of a variety of CPU cores and FPGA IPs. Our strategy significantly reduces the overhead to automatically compute the near-optimal chunksizes when compared to a previous state-of-the-art auto-tuned approach, which makes our approach more suitable for fine-grained applications. Additionally, our scheduler MultiFastFit has been designed to enable the efficient co-execution of work among compute devices in such a way that all the devices are busy while minimizing the load unbalance.Our approaches have been evaluated using four benchmarks carefully tuned for the low-power UltraScale+ platform. Our experiments demonstrate that the FastFit strategy always finds the near-optimal FPGA chunksize for any device configuration at a reasonable cost, even for fine-grained and irregular applications, and that heterogeneous CPU+FPGA co-executions that exploit all the compute devices are usually faster and more energy efficient than the CPU-only and FPGA-only executions. We have also compared MultiFastFit with other state-of-the-art scheduling strategies, finding that it outperforms other auto-tuned approach up to 2x and it achieves similar results to manually-tuned schedulers without requiring an offline search of the ideal CPU-FPGA partition or FPGA chunk granularity.

A Novel Methodology for Task Distribution in Heterogeneous Reconfigurable Computing System

Modern embedded systems are being modeled as Heterogeneous Reconfigurable Computing Systems (HRCS) where Reconfigurable Hardware i.e. Field Programmable Gate Array (FPGA) and soft core processors acts as computing elements. So, an efficient task distribution methodology is essential for obtaining high performance in modern embedded systems. In this paper, we present a novel methodology for task distribution called Minimum Laxity First (MLF) algorithm that takes the advantage of runtime reconfiguration of FPGA in order to effectively utilize the available resources. The MLF algorithm is a list based dynamic scheduling algorithm that uses attributes of tasks as well computing resources as cost function to distribute the tasks of an application to HRCS. In this paper, an on chip HRCS computing platform is configured on Virtex 5 FPGA using Xilinx EDK. The real time applications JPEG, OFDM transmitters are represented as task graph and then the task are distributed, statically as well dynamically, to the platform HRCS in order to evaluate the performance of the designed task distribution model. Finally, the performance of MLF algorithm is compared with existing static scheduling algorithms. The comparison shows that the MLF algorithm outperforms in terms of efficient utilization of resources on chip and also speedup an application execution.

A Case Study: Task Scheduling Methodologies for High Speed Computing Systems

High Speed computing meets ever increasing real-time computational demands through the leveraging of flexibility and parallelism. The flexibility is achieved when computing platform designed with heterogeneous resources to support multifarious tasks of an application where as task scheduling brings parallel processing. The efficient task scheduling is critical to obtain optimized performance in heterogeneous computing Systems (HCS). In this paper, we brought a review of various application scheduling models which provide parallelism for homogeneous and heterogeneous computing systems. In this paper, we made a review of various scheduling methodologies targeted to high speed computing systems and also prepared summary chart. The comparative study of scheduling methodologies for high speed computing systems has been carried out based on the attributes of platform & application as well. The attributes are execution time, nature of task, task handling capability, type of host & computing platform. Finally a summary chart has been prepared and it demonstrates that the need of developing scheduling methodologies for Heterogeneous Reconfigurable Computing Systems (HRCS) which is an emerging high speed computing platform for real time applications.

Mapping Adaptive Particle Filters to Heterogeneous Reconfigurable Systems

This article presents an approach for mapping real-time applications based on particle filters (PFs) to heterogeneous reconfigurable systems, which typically consist of multiple FPGAs and CPUs. A method is proposed to adapt the number of particles dynamically and to utilise runtime reconfigurability of FPGAs for reduced power and energy consumption. A data compression scheme is employed to reduce communication overhead between FPGAs and CPUs. A mobile robot localisation and tracking application is developed to illustrate our approach. Experimental results show that the proposed adaptive PF can reduce up to 99% of computation time. Using runtime reconfiguration, we achieve a 25% to 34% reduction in idle power. A 1U system with four FPGAs is up to 169 times faster than a single-core CPU and 41 times faster than a 1U CPU server with 12 cores. It is also estimated to be 3 times faster than a system with four GPUs.

A design flow for speeding-up dsp applications in heterogeneous reconfigurable systems

In this paper, we propose a method for speeding-up Digital Signal Processing applications by partitioning them between the reconfigurable hardware blocks of different granularity and mapping critical parts of applications on coarse-grain reconfigurable hardware. The reconfigurable hardware blocks are embedded in a heterogeneous reconfigurable system architecture. The fine-grain part is implemented by an embedded FPGA unit, while for the coarse-grain reconfigurable hardware our developed high-performance coarse-grain data-path is used. The design flow mainly consists of three steps; the analysis procedure, the mapping onto coarse-grain blocks, and the mapping onto the fine-grain hardware. In this work, the methodology is validated using five real-life applications; an OFDM transmitter, a medical imaging technique, a wavelet-based image compressor, a video compression scheme and a JPEG encoder. The experimental results show that the speedup, relative to an all-FPGA solution, ranges from 1.55 to 4.17 for the considered applications.

Micro-Task Processing in Heterogeneous Reconfigurable Systems

New reconfigurable computing architectures are introduced to overcome some of the limitations of conventional microprocessors and fine-grained reconfigurable devices (e.g., FPGAs). One of the new promising architectures are Configurable System-on-Chip (CSoC) solutions. They were designed to offer high computational performance for real-time signal processing and for a wide range of applications exhibiting high degrees of parallelism. The programming of such systems is an inherently challenging problem due to the lack of an programming model. This paper describes a novel heterogeneous system architecture for signal processing and data streaming applications. It offers high computational performance and a high degree of flexibility and adaptability by employing a micro Task Controller (mTC) unit in conjunction with programmable and configurable hardware. The hierarchically organized architecture provides a programming model, allows an efficient mapping of applications and is shown to be easy scalable to future VLSI technologies. Several mappings of commonly used digital signal processing algorithms for future telecommunication and multimedia systems and implementation results are given for a standard-cell ASIC design realization in 0.18 micron 6-layer UMC CMOS technology.

Reconfigurable Discrete Wavelet Transform Processor for Heterogeneous Reconfigurable Multimedia Systems

In this paper, a novel reconfigurable discrete wavelet transform processor architecture is proposed to meet the diverse computing requirements of future generation multimedia SoC. The proposed architecture mainly consists of reconfigurable processing element array and reconfigurable address generator, featuring dynamically reconfigurable capability where the wavelet filters and wavelet decomposition structures can be reconfigured as desired at run-time. The lifting-based reconfigurable processing element array possesses better computation efficiency than convolution-based architectures, and a systematic design method is provided to generate the hardware configurations of different wavelet filters for it. The reconfigurable address generator handles flexible address generation for data I/O access in different wavelet decomposition structures. A prototyping chip has been fabricated by TSMC 0.35 ?m 1P4M CMOS process. At 50 MHz, this chip can achieve at most 100 M pixels/sec transform throughput, together with energy efficiency and unique reconfigurability features, proving it to be a universal and extremely flexible computing engine for heterogeneous reconfigurable multimedia systems.

Model-Based Exploration of the Design Space for Heterogeneous Systems on Chip

The exploration of the design space for heterogeneous reconfigurable systems on chip (SoC) becomes more and more important. As modern SoCs include a variety of different architecture blocks, ensuring flexibility as well as highest performance, it is mandatory to prune the design space in an early stage of the design process in order to achieve short innovation cycles for new products. Therefore, the goal of this work is to provide estimations of implementation specific parameters like throughput rate, power dissipation and silicon area by means of cost functions. A concept for a model based exploration strategy supporting the design flow for heterogeneous SoCs is presented. In order to prove the feasibility of this exploration strategy, first of all operations were implemented on discrete components like DSPs, FPGAs or dedicated ASICs. Implementation parameters are provided for a variety of basic operations frequently required in digital signal processing. These implementation parameters serve as a basis for deriving models for the design space exploration concept.