R (langage) | EPFL Graph Search

R est un langage de programmation et un logiciel libre destiné aux statistiques et à la science des données soutenu par la R Foundation for Statistical Computing. Il fait partie de la liste des paquets GNU et est écrit en C, Fortran et R. GNU R est un logiciel libre distribué selon les termes de la licence GNU GPL. Le site officiel fournit des binaires pour Linux, Windows et macOS, et des portages existent pour d'autres systèmes d'exploitation. Le langage R est largement utilisé par les statisticiens, les data miners, data scientists pour le développement de logiciels statistiques et l'analyse des données. En , R est classé 19e dans l'index TIOBE qui mesure la popularité des langages de programmation. Histoire thumb|upright=1.5|R dans un Terminal sous Linux. R est une implémentation du langage de programmation S avec l'ajout de la portée lexicale, inspirée du Scheme, et d'un ramasse-miettes (informatique). Le langage S a été développé par John Chambers et ses collègues

Circuit Design, Architecture and CAD for RRAM-based FPGAs

Xifan Tang

Field Programmable Gate Arrays (FPGAs) have been indispensable components of embedded systems and datacenter infrastructures. However, energy efficiency of FPGAs has become a hard barrier preventing their expansion to more application contexts, due to two physical limitations: (1) The massive usage of routing multiplexers causes delay and power overheads as compared to ASICs. To reduce their power consumption, FPGAs have to operate at low supply voltage but sacrifice performance because the transistors drive degrade when working voltage decreases. (2) Using volatile memory technology forces FPGAs to lose configurations when powered off and to be reconfigured at each power on. Resistive Random Access Memories (RRAMs) have strong potentials in overcoming the physical limitations of conventional FPGAs. First of all, RRAMs grant FPGAs non-volatility, enabling FPGAs to be "Normally powered off, Instantly powered on". Second, by combining functionality of memory and pass-gate logic in one unique device, RRAMs can greatly reduce area and delay of routing elements. Third, when RRAMs are embedded into datpaths, the performance of circuits can be independent from their working voltage, beyond the limitations of CMOS circuits. However, researches and development of RRAM-based FPGAs are in their infancy. Most of area and performance predictions were achieved without solid circuit-level simulations and sophisticated Computer Aided Design (CAD) tools, causing the predicted improvements to be less convincing. In this thesis,we present high-performance and low-power RRAM-based FPGAs fromtransistorlevel circuit designs to architecture-level optimizations and CAD tools, using theoretical analysis, industrial electrical simulators and novel CAD tools. We believe that this is the first systematic study in the field, covering: From a circuit design perspective, we propose efficient RRAM-based programming circuits and routing multiplexers through both theoretical analysis and electrical simulations. The proposed 4T(ransitor)1R(RAM) programming structure demonstrates significant improvements in programming current, when compared to most popular 2T1R programming structure. 4T1R-based routingmultiplexer designs are proposed by considering various physical design parasitics, such as intrinsic capacitance of RRAMs and wells doping organization. The proposed 4T1R-based multiplexers outperformbest CMOS implementations significantly in area, delay and power at both nominal and near-Vt regime. From a CAD perspective, we develop a generic FPGA architecture exploration tool, FPGASPICE, modeling a full FPGA fabric with SPICE and Verilog netlists. FPGA-SPICE provides different levels of testbenches and techniques to split large SPICE netlists, in order to obtain better trade-off between simulation time and accuracy. FPGA-SPICE can capture area and power characteristics of SRAM-based and RRAM-based FPGAs more accurately than the currently best analyticalmodels. From an architecture perspective, we propose architecture-level optimizations for RRAMbased FPGAs and quantify their minimumrequirements for RRAM devices. Compared to the best SRAM-based FPGAs, an optimized RRAM-based FPGA architecture brings significant reduction in area, delay and power respectively. In particular, RRAM-based FPGAs operating in the near-Vt regime demonstrate a 5x power improvement without delay overhead as compared to optimized SRAM-based FPGA operating at nominal working voltage.

EPFL2017

Resistive random access memory based multiplexers and field programmable gate arrays

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Edouard Giacomin, Gain Kim, Xifan Tang

Resistive random access memory (RRAM) based multiplexers and field programmable gate arrays (FPGAs) are provided. The RRAM-based multiplexers and FPGAs include a 4T1R programming structure to program the RRAMs. The programming structure includes two programming transistors connected between the power supply and the top electrode of the RRAM and two programming transistors connected between the power supply and the bottom electrode of the RRAM. The programming transistors are used to set and rest the RRAMs. In the RRAM-based multiplexer programming transistors connected to the bottom electrodes are shared between a plurality of RRAMs. The shared programming transistors and an output inverter of the RRAM are provided in a deep N-well of the RRAM-based multiplexer. The programming transistors connected to the top electrodes of the RRAMs and a plurality of input inverters are provided in a regular well of the RRAM-based multiplexer.

2018

A Study on the Programming Structures for RRAM-based FPGA Architectures

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Gain Kim, Xifan Tang

Field Programmable Gate Arrays (FPGAs) can benefit non-volatility and high-performance by exploiting Resistive Random Access Memories (RRAMs). In RRAM-based FPGAs, the memories do not only replace the SRAMs and store configurations, but they can also replace the transmission gates and propagate datapath signals. The high-performance achievable by RRAM-based FPGAs comes from the fact that the on-resistance of the memory devices RmathLRS is smaller than the equivalent resistance of a transmission gate. Efficient programming structures for RRAMs should provide high current density with a small area footprint, to obtain a low Rmath. In this paper, we first examine the efficiency of the widely-used 2Transistor/1RRAM (2T1R) programming structure and identify four major limitations of the 2T1R structure. To overcome these limitations, we propose a 2Transmission-Gates/1RRAM (2TG1R) and a 4Transistor/1RRAM (4T1R) programming structures. We perform both theoretical analysis and electrical simulations on the evaluated programming structures. 4T1R programming structure is the best in terms of current density with 1.4 x and 1.1 x as compared to 2T1R and 2TG1R counterparts, respectively. We also investigate the effect of boosting the programming voltage Vmathprog of the programming structures. Experimental results show that boosting Vmathprog for all the programming structures improves driving current of the evaluated programming structures by 3 x and area efficiency by 1.7 x on average.

Ieee-Inst Electrical Electronics Engineers Inc2016

Circuit Design, Architecture and CAD for RRAM-based FPGAs

Xifan Tang

EPFL2017