NetFPGA Hardware Modules for Input, Output and EWMA Bit-Rate Computation

NetFPGA is a hardware board that it is becoming increasingly popular in various research areas. It is a hardware customizable router and it can be used to study, implement and test new protocols and techniques directly in hardware. It allows researchers to experience a more real experiment environment. In this paper we present a work about the design and development of four new modules built on top of the NetFPGA Reference Router design. In particular, they compute the input and output bit rate run time and provide an estimation of the input bit rate based on an EWMA filter. Moreover we extended the rate limiter module which is embedded within the output queues in order to test our improved Reference Router. Along the paper we explain in detail each module as far as the architecture and the implementation are concerned. Furthermore, we created a testing environment which show the effectiveness and effciency of our module

Reducing the Overhead of BCH Codes: New Double Error Correction Codes

[EN] The Bose-Chaudhuri-Hocquenghem (BCH) codes are a well-known class of powerful error correction cyclic codes. BCH codes can correct multiple errors with minimal redundancy. Primitive BCH codes only exist for some word lengths, which do not frequently match those employed in digital systems. This paper focuses on double error correction (DEC) codes for word lengths that are in powers of two (8, 16, 32, and 64), which are commonly used in memories. We also focus on hardware implementations of the encoder and decoder circuits for very fast operations. This work proposes new low redundancy and reduced overhead (LRRO) DEC codes, with the same redundancy as the equivalent BCH DEC codes, but whose encoder, and decoder circuits present a lower overhead (in terms of propagation delay, silicon area usage and power consumption). We used a methodology to search parity check matrices, based on error patterns, in order to design the new codes. We implemented and synthesized them, and compared their results with those obtained for the BCH codes. Our implementation of the decoder circuits achieved reductions between 2.8% and 8.7% in the propagation delay, between 1.3% and 3.0% in the silicon area, and between 15.7% and 26.9% in the power consumption. Therefore, we propose LRRO codes as an alternative for protecting information against multiple errors.This research was supported in part by the Spanish Government, project TIN2016-81075-R, by Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion, Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), project 20190032, and by the Institute of Information and Communication Technologies (ITACA).Saiz-Adalid, L.; Gracia-Morán, J.; Gil Tomás, DA.; Baraza Calvo, JC.; Gil, P. (2020). Reducing the Overhead of BCH Codes: New Double Error Correction Codes. Electronics. 9(11):1-14. https://doi.org/10.3390/electronics9111897S114911Fujiwara, E. (2005). Code Design for Dependable Systems. doi:10.1002/0471792748Xinmiao, Z. (2017). VLSI Architectures for Modern Error-Correcting Codes. doi:10.1201/b18673Bose, R. C., & Ray-Chaudhuri, D. K. (1960). On a class of error correcting binary group codes. Information and Control, 3(1), 68-79. doi:10.1016/s0019-9958(60)90287-4Chen, P., Zhang, C., Jiang, H., Wang, Z., & Yue, S. (2015). High performance low complexity BCH error correction circuit for SSD controllers. 2015 IEEE International Conference on Electron Devices and Solid-State Circuits (EDSSC). doi:10.1109/edssc.2015.7285089IEEE 802.3-2018 - IEEE Standard for Ethernethttps://standards.ieee.org/standard/802_3-2018.htmlH.263: Video Coding for Low Bit Rate Communicationhttps://www.itu.int/rec/T-REC-H.263/enVangelista, L., Benvenuto, N., Tomasin, S., Nokes, C., Stott, J., Filippi, A., … Morello, A. (2009). Key technologies for next-generation terrestrial digital television standard DVB-T2. 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DEC ECC design to improve memory reliability in Sub-100nm technologies. 2008 15th IEEE International Conference on Electronics, Circuits and Systems. doi:10.1109/icecs.2008.4674921Saiz-Adalid, L.-J., Gracia-Moran, J., Gil-Tomas, D., Baraza-Calvo, J.-C., & Gil-Vicente, P.-J. (2019). Ultrafast Codes for Multiple Adjacent Error Correction and Double Error Detection. IEEE Access, 7, 151131-151143. doi:10.1109/access.2019.2947315Saiz-Adalid, L.-J., Gil-Vicente, P.-J., Ruiz-García, J.-C., Gil-Tomás, D., Baraza, J.-C., & Gracia-Morán, J. (2013). Flexible Unequal Error Control Codes with Selectable Error Detection and Correction Levels. Computer Safety, Reliability, and Security, 178-189. doi:10.1007/978-3-642-40793-2_17Saiz-Adalid, L.-J., Reviriego, P., Gil, P., Pontarelli, S., & Maestro, J. A. (2015). MCU Tolerance in SRAMs Through Low-Redundancy Triple Adjacent Error Correction. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 23(10), 2332-2336. doi:10.1109/tvlsi.2014.2357476Gracia-Moran, J., Saiz-Adalid, L. J., Gil-Tomas, D., & Gil-Vicente, P. J. (2018). Improving Error Correction Codes for Multiple-Cell Upsets in Space Applications. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 26(10), 2132-2142. doi:10.1109/tvlsi.2018.2837220Cadence: Computational Software for Intelligent System Designhttps://www.cadence.comStine, J. E., Castellanos, I., Wood, M., Henson, J., Love, F., Davis, W. R., … Jenkal, R. (2007). FreePDK: An Open-Source Variation-Aware Design Kit. 2007 IEEE International Conference on Microelectronic Systems Education (MSE’07). doi:10.1109/mse.2007.44NanGate FreePDK45 Open Cell Libraryhttp://www.nangate.com/?page_id=232

Air Force Institute of Technology Research Report 2016

This Research Report presents the FY16 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Neural network computing using on-chip accelerators

The use of neural networks, machine learning, or artificial intelligence, in its broadest and most controversial sense, has been a tumultuous journey involving three distinct hype cycles and a history dating back to the 1960s. Resurgent, enthusiastic interest in machine learning and its applications bolsters the case for machine learning as a fundamental computational kernel. Furthermore, researchers have demonstrated that machine learning can be utilized as an auxiliary component of applications to enhance or enable new types of computation such as approximate computing or automatic parallelization. In our view, machine learning becomes not the underlying application, but a ubiquitous component of applications. This view necessitates a different approach towards the deployment of machine learning computation that spans not only hardware design of accelerator architectures, but also user and supervisor software to enable the safe, simultaneous use of machine learning accelerator resources. In this dissertation, we propose a multi-transaction model of neural network computation to meet the needs of future machine learning applications. We demonstrate that this model, encompassing a decoupled backend accelerator for inference and learning from hardware and software for managing neural network transactions can be achieved with low overhead and integrated with a modern RISC-V microprocessor. Our extensions span user and supervisor software and data structures and, coupled with our hardware, enable multiple transactions from different address spaces to execute simultaneously, yet safely. Together, our system demonstrates the utility of a multi-transaction model to increase energy efficiency improvements and improve overall accelerator throughput for machine learning applications

Air Force Institute of Technology Research Report 2019

This Research Report presents the FY19 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Air Force Institute of Technology Research Report 2017

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Tuning the Computational Effort: An Adaptive Accuracy-aware Approach Across System Layers

This thesis introduces a novel methodology to realize accuracy-aware systems, which will help designers integrate accuracy awareness into their systems. It proposes an adaptive accuracy-aware approach across system layers that addresses current challenges in that domain, combining and tuning accuracy-aware methods on different system layers. To widen the scope of accuracy-aware computing including approximate computing for other domains, this thesis presents innovative accuracy-aware methods and techniques for different system layers. The required tuning of the accuracy-aware methods is integrated into a configuration layer that tunes the available knobs of the accuracy-aware methods integrated into a system