A survey of DA techniques for PLD and FPGA based systems

Programmable logic devices (PLDs) are gaining in acceptance, of late, for designing systems of all complexities ranging from glue logic to special purpose parallel machines. Higher densities and integration levels are made possible by the new breed of complex PLDs and FPGAs. The added complexities of these devices make automatic computer aided tools indispensable for achieving good performance and a high usable gate-count. In this article, we attempt to present in an unified manner, the different tools and their underlying algorithms using an example of a vending machine controller as an illustrative example. Topics covered include logic synthesis for PLDs and FPGAs along with an in-depth survey of important technology mapping, partitioning and place and route algorithms for different FPGA architectures.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31206/1/0000108.pd

A framework to explore low-power architecture and variability-aware timing estimation of FPGAs

Master'sMASTER OF ENGINEERIN

A Field Programmable Gate Array Architecture for Two-Dimensional Partial Reconfiguration

Reconfigurable machines can accelerate many applications by adapting to their needs through hardware reconfiguration. Partial reconfiguration allows the reconfiguration of a portion of a chip while the rest of the chip is busy working on tasks. Operating system models have been proposed for partially reconfigurable machines to handle the scheduling and placement of tasks. They are called OS4RC in this dissertation. The main goal of this research is to address some problems that come from the gap between OS4RC and existing chip architectures and the gap between OS4RC models and practical applications. Some existing OS4RC models are based on an impractical assumption that there is no data exchange channel between IP (Intellectual Property) circuits residing on a Field Programmable Gate Array (FPGA) chip and between an IP circuit and FPGA I/O pins. For models that do not have such an assumption, their inter-IP communication channels have severe drawbacks. Those channels do not work well with 2-D partial reconfiguration. They are not suitable for intensive data stream processing. And frequently they are very complicated to design and very expensive. To address these problems, a new chip architecture that can better support inter-IP and IP-I/O communication is proposed and a corresponding OS4RC kernel is then specified. The proposed FPGA architecture is based on an array of clusters of configurable logic blocks, with each cluster serving as a partial reconfiguration unit, and a mesh of segmented buses that provides inter-IP and IP-I/O communication channels. The proposed OS4RC kernel takes care of the scheduling, placement, and routing of circuits under the constraints of the proposed architecture. Features of the new architecture in turns reduce the kernel execution times and enable the runtime scheduling, placement and routing. The area cost and the configuration memory size of the new chip architecture are calculated and analyzed. And the efficiency of the OS4RC kernel is evaluated via simulation using three different task models

Design Methodologies and CAD Tools for Leakage Power Optimization in FPGAs

The scaling of the CMOS technology has precipitated an exponential increase in both subthreshold and gate leakage currents in modern VLSI designs. Consequently, the contribution of leakage power to the total chip power dissipation for CMOS designs is increasing rapidly, which is estimated to be 40% for the current technology generations and is expected to exceed 50% by the 65nm CMOS technology. In FPGAs, the power dissipation problem is further aggravated when compared to ASIC designs because FPGA use more transistors per logic function when compared to ASIC designs. Consequently, solving the leakage power problem is pivotal to devising power-aware FPGAs in the nanometer regime. This thesis focuses on devising both architectural and CAD techniques for leakage mitigation in FPGAs. Several CAD and architectural modifications are proposed to reduce the impact of leakage power dissipation on modern FPGAs. Firstly, multi-threshold CMOS (MTCMOS) techniques are introduced to FPGAs to permanently turn OFF the unused resources of the FPGA, FPGAs are characterized with low utilization percentages that can reach 60%. Moreover, such architecture enables the dynamic shutting down of the FPGA idle parts, thus reducing the standby leakage significantly. Employing the MTCMOS technique in FPGAs requires several changes to the FPGA architecture, including the placement and routing of the sleep signals and the MTCMOS granularity. On the CAD level, the packing and placement stages are modified to allow the possibility of dynamically turning OFF the idle parts of the FPGA. A new activity generation algorithm is proposed and implemented that aims to identify the logic blocks in a design that exhibit similar idleness periods. Several criteria for the activity generation algorithm are used, including connectivity and logic function. Several versions of the activity generation algorithm are implemented to trade power savings with runtime. A newly developed packing algorithm uses the resulting activities to minimize leakage power dissipation by packing the logic blocks with similar or close activities together. By proposing an FPGA architecture that supports MTCMOS and developing a CAD tool that supports the new architecture, an average power savings of 30% is achieved for a 90nm CMOS process while incurring a speed penalty of less than 5%. This technique is further extended to provide a timing-sensitive version of the CAD flow to vary the speed penalty according to the criticality of each logic block. Secondly, a new technique for leakage power reduction in FPGAs based on the use of input dependency is developed. Both subthreshold and gate leakage power are heavily dependent on the input state. In FPGAs, the effect of input dependency is exacerbated due to the use of pass-transistor multiplexer logic, which can exhibit up to 50% variation in leakage power due to the input states. In this thesis, a new algorithm is proposed that uses bit permutation to reduce subthreshold and gate leakage power dissipation in FPGAs. The bit permutation algorithm provides an average leakage power reduction of 40% while having less than 2% impact on the performance and no penalty on the design area. Thirdly, an accurate probabilistic power model for FPGAs is developed to quantify the savings from the proposed leakage power reduction techniques. The proposed power model accounts for dynamic, short circuit, and leakage power (including both subthreshold and gate leakage power) dissipation in FPGAs. Moreover, the power model accounts for power due to glitches, which accounts for almost 20% of the dynamic power dissipation in FPGAs. The use of probabilities in the power model makes it more computationally efficient than the other FPGA power models in the literature that rely on long input sequence simulations. One of the main advantages of the proposed power model is the incorporation of spatial correlation while estimating the signal probability. Other probabilistic FPGA power models assume spatial independence among the design signals, thus overestimating the power calculations. In the proposed model, a probabilistic model is proposed for spatial correlations among the design signals. Moreover, a different variation is proposed that manages to capture most of the spatial correlations with minimum impact on runtime. Furthermore, the proposed power model accounts for the input dependency of subthreshold and gate leakage power dissipation. By comparing the proposed power model to HSpice simulation, the estimated power is within 8% and is closer to HSpice simulations than other probabilistic FPGA power models by an average of 20%

Interconnect yield analysis and fault tolerance for field programmable gate arrays

Imperial Users onl

Dynamically reconfigurable asynchronous processor

The main design requirements for today's mobile applications are: · high throughput performance. · high energy efficiency. · high programmability. Until now, the choice of platform has often been limited to Application-Specific Integrated Circuits (ASICs), due to their best-of-breed performance and power consumption. The economies of scale possible with these high-volume markets have traditionally been able to hide the high Non-Recurring Engineering (NRE) costs required for designing and fabricating new ASICs. However, with the NREs and design time escalating with each generation of mobile applications, this practice may be reaching its limit. Designers today are looking at programmable solutions, so that they can respond more rapidly to changes in the market and spread costs over several generations of mobile applications. However, there have been few feasible alternatives to ASICs: Digital Signals Processors (DSPs) and microprocessors cannot meet the throughput requirements, whereas Field-Programmable Gate Arrays (FPGAs) require too much area and power. Coarse-grained dynamically reconfigurable architectures offer better solutions for high throughput applications, when power and area considerations are taken into account. One promising example is the Reconfigurable Instruction Cell Array (RICA). RICA consists of an array of cells with an interconnect that can be dynamically reconfigured on every cycle. This allows quite complex datapaths to be rendered onto the fabric and executed in a single configuration - making these architectures particularly suitable to stream processing. Furthermore, RICA can be programmed from C, making it a good fit with existing design methodologies. However the RICA architecture has a drawback: poor scalability in terms of area and power. As the core gets bigger, the number of sequential elements in the array must be increased significantly to maintain the ability to achieve high throughputs through pipelining. As a result, a larger clock tree is required to synchronise the increased number of sequential elements. The clock tree therefore takes up a larger percentage of the area and power consumption of the core. This thesis presents a novel Dynamically Reconfigurable Asynchronous Processor (DRAP), aimed at high-throughput mobile applications. DRAP is based on the RICA architecture, but uses asynchronous design techniques - methods of designing digital systems without clocks. The absence of a global clock signal makes DRAP more scalable in terms of power and area overhead than its synchronous counterpart. The DRAP architecture maintains most of the benefits of custom asynchronous design, whilst also providing programmability via conventional high-level languages. Results show that the DRAP processor delivers considerably lower power consumption when compared to a market-leading Very Long Instruction Word (VLIW) processor and a low-power ARM processor. For example, DRAP resulted in a reduction in power consumption of 20 times compared to the ARM7 processor, and 29 times compared to the TIC64x VLIW, when running the same benchmark capped to the same throughput and for the same process technology (0.13μm). When compared to an equivalent RICA design, DRAP was up to 22% larger than RICA but resulted in a power reduction of up to 1.9 times. It was also capable of achieving up to 2.8 times higher throughputs than RICA for the same benchmarks

Circuit Clustering for Cluster-based FPGAs Using Novel Multiobjective Genetic Algorithms

Circuit clustering is one of the most crucial steps in a post-synthesis FPGA CAD flow. It attempts to efficiently fit synthesised logic functions into FPGA logic clusters. On a FPGA, different clusterings result in different circuit mappings, which affect FPGA utilisation, routability and timing, and therefore impact the circuit performance. This research proposes the use of a Multi Objective Genetic Algorithm (MOGA) as a methodology to solve the cluster-based FPGA circuit clustering problem. Four alternative approaches based on MOGA methods are proposed in this research: RVPack is inspired by the stochastic feature that exists in Evolutionary Algorithms (EAs). GGAPack, GGAPack2, DBPack and HYPack, T-HYPack (Timing-driven HYPack) are then proposed and developed, which are fully customised MOGA-based circuit clustering methods. GGAPack clusters a circuit using a top-down perspective, and DBPack uses a new bottom-up perspective. HYPack combines GGAPack and HYPack -- a hybrid method. According to experimental results, a few conclusions are drawn: It is possible to improve the performance of the greedy algorithm based circuit clustering methods by incorporating randomness. The performance of MOGA based top-down clustering is poor; however, using MOGA to cluster a circuit from a bottom-up perspective can produce better solutions. T-HYPack clustered circuit has the best timing performance compared with state-of-the-art methods. The experimental results also reflect a wider potential for using GAs to solve FPGA circuit mapping problems