This paper describes a non-volatile reprogrammable FPGA fabric, whose configuration data are provided directly by flash memory. The fabric is optimized for low-cost, low-power applications, leveraging the density of flash and the elimination of conventional configuration SRAM and its attendant static power. After surveying the necessary background on flash and its application to FPGAs, the 1T flash cell is described along with relevant novel aspects of the fabric architecture. The addition of a third level of switching between inter-cluster signals and logic inputs helps to reduce area and raise typical utilization above 95%. Despite the longer signal path, performance is maintained by synergism between the improved routing flexibility and extreme minimization of the fastest LUT input delay. Test cost is reduced by built-in circuits that can test all switches without reprogramming the flash memory. The fabric has been implemented in a 65nm CMOS embedded flash process.

This paper presents a technology mapping algorithm for field-programmable gate array architectures with dual supply voltages (Vdds) for power optimization. This is done with the guarantee that the mapping depth of the circuit will not increase compared to the circuit with a single Vdd. This paper also presents an enhanced clustering algorithm that considers dual supply voltages, honoring the dual-Vdd mapping solution. To carry out various comparisons, we first design a single-Vdd mapping algorithm, named SVmap-2, which achieves a 3.8% total power reduction (15.6% dynamic power reduction) over a previously published low-power mapping algorithm, Emap . We then show that our dual-Vdd mapping algorithm, named DVmap-2, can further improve total power savings by 12.8% over SVmap-2, with a 52.7% dynamic power reduction. Compared to the early single-Vdd version SVmap , DVmap-2 is 14.3% better for total power reduction. This is achieved through an ideal selection of the low-Vdd/high-Vdd ratio and the consideration of various voltage changing scenarios during the mapping process.

Device optimization considering supply voltage Vdd and threshold voltage Vt has little chip-area increase but a great impact on power and performance in the nanometer technology. This paper studies simultaneous evaluation of device and architecture optimization for field-programmable gate arrays (FPGAs). We first develop an efficient yet accurate timing and power evaluation method called a trace-based model. By collecting trace information from a cycle-accurate simulation of placed and routed FPGA benchmark circuits and reusing the trace for different Vdds and Vts, we enable device and architecture cooptimization considering hundreds of device and architecture combinations. Compared to the baseline FPGA architecture, which uses the Versatile Place and Route architecture model and the same lookup table and cluster sizes as those used by the Xilinx Virtex-II, Vdd suggested by the International Technology Roadmap for Semiconductor, Vt optimized with respect to the preceding architecture, and Vdd architecture and device cooptimization can reduce the energy-delay product (ED) by 20.5% and the chip area by 23.3%. Furthermore, considering the power gating of unused logic blocks and interconnect switches (in this case, sleep transistor size is a parameter of device tuning), our co-optimization reduces ED by 55.0% and the chip area by 8.2% compared to the baseline FPGA architecture. To the best of our knowledge, this is the first in-depth study in the literature on architecture and device cooptimization for FPGAs.

Power reduction is of growing importance for field-programmable gate arrays (FPGAs). In this paper, we apply programmable supply voltage (Vdd) to reduce FPGA power. We first design FPGA logic fabrics using dual-Vdd levels and show that field-programmable power supply is required to obtain a satisfactory power-versus-performance tradeoff. We further design FPGA interconnect fabrics for fine-grained Vdd programmability with minimal increase of the number of configuration static-random-access-memory cells. With a simple yet practical computer-aided design flow to leverage the field-programmable dual-Vdd logic and interconnect fabrics, we carry out a highly quantitative study using placed and routed benchmark circuits, and delay, power, and area models obtained from detailed circuit designs. Compared to single-Vdd FPGAs with the Vdd level suggested by the International Technology Roadmap for Semiconductors for 100-nm technology, field-programmable dual-Vdd FPGAs reduce the total power by 47.61% and the energy-delay product by 27.36%

Power has become an increasingly important design constraint for FPGAs in nanometer technologies, and global interconnects should be the focus of FPGA power reduction as they consume more power than logic cells. We design area-efficient circuits for programmable fine-grained power-gating of individual unused interconnect switches, and reduce interconnect leakage power dramatically because the interconnect switches have an intrinsically low utilization rate for the purpose of programmability. The low leakage interconnect via power-gating reduces total power by 38.18% for the FPGA in 100nm technology. Furthermore, it enables interconnect dynamic power reduction. We design a routing channel containing abundant or duplicated routing tracks with pre-determined high and low Vdd, and develop routing algorithm using low Vdd for non-critical routing to reduce dynamic power. The track-duplicated routing channel has small leakage power and increase the FPGA power reduction to 45.00%.

Device optimization considering supply voltage Vdd and threshold voltage Vt tuning does not increase chip area but has a great impact on power and performance in the nanometer technology. This paper studies the simultaneous evaluation of device and architecture optimization for FPGA. We first develop an efficient yet accurate timing and power evaluation method, called trace-based model. By collecting trace information from cycle-accurate simulation of placed and routed FPGA benchmark circuits and re-using the trace for different Vdd and Vt, we enable the device and architecture co-optimization for hundreds of combinations. Compared to the baseline FPGA which has the architecture same as the commercial FPGA used by Xilinx, and has Vdd suggested by ITRS but Vt optimized by our device optimization, architecture and device co-optimization can reduce energy-delay product by 20.5% without any chip area increase compared to the conventional FPGA architecture. Furthermore, considering power-gating of unused logic blocks and interconnect switches, our co-optimization method reduces energy-delay product by 54.7% and chip area by 8.3%. To the best of our knowledge, this is the first in-depth study on architecture and device co-optimization for FPGAs.

Context-aware applications pose new challenges, including a need for new computational models, uncertainty management, and efficient optimization under uncertainty. Uncertainty can arise at two levels: multiple and single tasks. When a mobile user changes environments, the context changes resulting in the possibility of the user requesting tasks which are specific for the new environment. However as the user moves these requested tasks may no longer be context relevant. Additionally, the runtime of each task is often highly dependent on the input data. We introduce an hierarchical multi-resolution statistical task model that captures relevant aspects at the task and intertask levels, and captures not only uncertainty, but also introduces the notion of utility for the user. We have developed a system of nonparametric statistical techniques for modeling the runtime of a specific task. This model is a framework where we define problems of design and optimization of statistical soft real-time systems (SSRTS). The main algorithmic novelty is a cumulative potential-based task scheduling heuristic for maximizing utility. The heuristic conducts global optimization and induces low runtime overhead. We demonstrate the effectiveness of the scheduling heuristic using a Trimaran-based evaluation platform.

Vdd-programmable FPGAs have been proposed recently to reduce FPGA power, where Vdd levels can be customized for different circuit elements and unused circuit elements can be power-gated. In this paper, we first develop an accurate FPGA power model and then design novel Vdd-programmable interconnect switches with minimum number of configuration SRAM cells. Applying our power model to placed and routed benchmark circuits, we evaluate Vdd-programmable FPGA architecture using the new switches. The best architecture in our study uses Vdd-programmable logic blocks and Vdd-gateable interconnects. Compared to the baseline architecture similar to the leading commercial architecture, the best architecture reduces the minimal energy-delay product by 44.14% with 48% area overhead and 3% SRAM cell increase. Our evaluation results also show that LUT size 4 always gives the lowest energy consumption while LUT size 7 always leads to the highest performance for all evaluated architectures.

This paper studies power modeling for field programmable gate arrays (FPGAs) and investigates FPGA power characteristics in nanometer technologies. Considering both dynamic and leakage power, a mixed-level power model that combines switch-level models for interconnects and macromodels for look-up tables (LUTs) is developed. Gate-level netlists back-annotated with postlayout capacitances and delays are generated and cycle-accurate power simulation is performed using the mixed-level power model. The resulting power analysis framework is named as fpgaEVA-LP2. Experiments show that fpgaEVA-LP2 achieves high fidelity compared to SPICE simulation, and the absolute error is merely 8% on average. fpgaEVA-LP2 can be used to examine the power impact of FPGA circuits, architectures, and CAD algorithms, and it is used to study the power characteristics of existing FPGA architectures in this paper. It is shown that interconnect power is dominant and leakage power is significant in nanometer technologies. In addition, tuning cluster and LUT sizes lead to 1.7/spl times/ energy difference and 0.8/spl times/ delay difference between the resulting min-energy and min-delay FPGA architectures, and FPGA area and power are reduced at the same time by tuning the cluster and LUT sizes. The existing commercial architectures are similar to the min-energy (and min-area at the same time) architecture according to this study. Therefore, innovative FPGA circuits, architectures, and CAD algorithms, for example, considering programmable power supply voltage, are needed to further reduce FPGA power.

Field programmable gate arrays (FPGAs) with supply voltage (Vdd) programmability have been proposed recently to reduce FPGA power, where the Vdd-level can be customized for FPGA circuit elements and unused circuit elements can be power-gated. In this paper, we first design novel Vdd-programmable and Vdd-gateable interconnect switches with minimal number of configuration SRAM cells. We then evaluate Vdd-programmable FPGA architectures using the new switches. The best architecture in our study uses Vdd-programmable logic blocks and Vdd-gateable interconnects. Compared to the baseline architecture similar to the leading commercial architecture, our best architecture reduces the minimal energy-delay product by 54.39% with 17% more area and 3% more configuration SRAM cells. Our evaluation results also show that LUT size 4 gives the lowest energy consumption, and LUT size 7 leads to the highest performance, both for all evaluated architectures.

Power optimization is of growing importance for FPGAs in nanometer technologies. Considering dual-Vdd technique, we show that configurable power supply is required to obtain a satisfactory performance and power tradeo#. We design FPGA circuits and logic fabrics using configurable dualVdd and develop the corresponding CAD flow to leverage such circuits and logic fabrics. We then carry out a highly quantitative study using area, delay and power models obtained from detailed circuit design and SPICE simulation in 100nm technology. Compared to single-Vdd FPGAs with optimized Vdd level for the same target clock frequency, configurable dual-Vdd FPGAs with full and partial supply programmability for logic blocks reduce logic power by 35.46% and 28.62% respectively and reduce total FPGA power by 14.29% and 9.04% respectively. To the best of our knowledge, it is the first in-depth study on FPGAs with configurable dual-Vdd for power reduction.

In this paper we study the technology mapping problem of FPGA architectures with dual supply voltages (Vdds) for power optimization. This is done with the guarantee that the mapping depth of the circuit will not increase compared to the circuit with a single Vdd. We first design a single-Vdd mapping algorithm that achieves better power results than the latest published low-power mapping algorithms. We then show that our dual-Vdd mapping algorithm can further improve power savings by up to 11.6% over the single-Vdd mapper. In addition, we investigate the best low-Vdd/high-Vdd ratio for the largest power reduction among several dual-Vdd combinations. To our knowledge, this is the first work on dual-Vdd mapping for FPGA architectures.

Traditional FPGAs use uniform supply voltage Vdd and uniform threshold voltage Vt. We propose to use pre-defined dual-Vdd and dual-Vt fabrics to reduce FPGA power. We design FPGA circuits with dual-Vdd/dual-Vt to effectively reduce both dynamic power and leakage power, and define dual-Vdd/dual-Vt FPGA fabrics based on the profiling of benchmark circuits. We further develop CAD algorithms including power-sensitivity based voltage assignment and simulated-annealing based placement to leverage such fabrics. Compared to the conventional fabric using uniform Vdd/Vt at the same target clock frequency, our new fabric using dual Vt achieves 9% to 20% power reduction. However, the pre-defined FPGA fabric using both dual Vdd and dual Vt only achieves on average 2% extra power reduction. It is because that the pre-designed dual-Vdd layout pattern introduces non-negligible performance penalty. Therefore, programmability of supply voltage is needed to achieve significant power saving for dual-Vdd FPGAs. To our best knowledge, it is the first in-depth study on applying both dual-Vdd and dual-Vt to FPGA considering circuits, fabrics and CAD algorithms.

Power is an increasingly important design constraint for FPGAs in nanometer technologies. Because interconnect power is dominant in FPGAs, we design Vdd-programmable interconnect fabric to reduce FPGA interconnect power. There are three Vdd states for interconnect switches: high Vdd, low Vdd and power-gating. We develop a simple design flow to apply high Vdd to critical paths and low Vdd to non-critical paths and to power gate unused interconnect switches. We carry out a highly quantitative study by placing and routing benchmark circuits in 100 nm technology to illustrate the power saving. Compared to single-Vdd FPGAs with optimized but nonprogrammable Vdd level for the same target clock frequency, our new FPGA fabric on average reduces interconnect power by 56.51% and total FPGA power by 50.55%. Due to the highly low utilization rate of routing switches, majority of the power reduction is achieved by power gating unused routing buffers. In contrast, recent work that considers Vdd programmability only for logic fabric reduces total FPGA power merely by 14.29%. To the best of our knowledge, it is the first in-depth study on Vdd programmability for FPGA interconnect power reduction.

This paper presents a flexible FPGA architecture evaluation framework, named fpgaEVA-LP, for power efficiency analysis of LUT-based FPGA architectures. Our work has several contributions: (i) We develop a mixed-level FPGA power model that combines switch-level models for interconnects and macromodels for LUTs; (ii) We develop a tool that automatically generates a back-annotated gate-level netlist with post-layout extracted capacitances and delays; (iii) We develop a cycle-accurate power simulator based on our power model. It carries out gate-level simulation under real delay model and is able to capture glitch power; (iv) Using the framework fpgaEVA-LP, we study the power efficiency of FPGAs, in 0.10um technology, under various settings of architecture parameters such as LUT sizes, cluster sizes and wire segmentation schemes and reach several important conclusions. We also present the detailed power consumption distribution among different FPGA components and shed light on the potential opportunities of power optimization for future FPGA designs (e.g., ≤: 0.10um technology).

In this paper, we present power models with clock and temperature scaling, and develop the first of its type coupled thermal and power simulation with temperature-dependent leakage power model at micro-architecture level. We show that leakage energy and total energy can be different by up to 2.5X and 2X for temperatures between 90°C and 130°C, respectively. Given such big energy variations, no power model at microarchitecture level is accurate without considering temperature dependent leakage models.

As semiconductor technology scales down, the leakage power will soon become comparable to the dynamic power. To reduce both dynamic and leakage power, power gating in addition to clock gating should be used because clock gating saves only dynamic power. The knowledge of maximum current is needed to design high-performance and reliable circuits using power gating. However, all existing techniques for maximum current estimation are not applicable to power gating. In this paper, we study the maximum current estimation problem considering power gating. We develop two algorithms based on automatic test pattern generation (ATPG), and apply them to ISCAS'85 benchmarks. Experiments show that our new estimation algorithms can finish the largest benchmark circuit within ten seconds, and achieve up to 87% larger current when compared to an existing ATPG-based estimation algorithm that is able to obtain maximum current estimation 6% less than the theoretical maximum current without considering power gating. This implies that power gating may lead to a larger maximum current when compared to the normal maximum switching current, and open a new avenue for maximum current estimation as well as circuit reliability research.