algorithmics and modular computations, Theory of Codes and Cryptography (3).From an analytical 1. RE Blahut. Theory and practice of error control codes. eecs.uottawa.ca/∼yongacog/courses/coding/ (3) R.E. Blahut,Theory and Practice of Error Control Codes, Addison Wesley, 1983. QA 268. Cached. Download as a PDF 457, Theory and Practice of Error Control CodesBlahut 1984 (Show Context). Citation Context..ontinued fractions.

Theory and practice of error control codes

A common way of representing processor performance is to use Cycles per Instruction (CPI) `stacks' which break performance into a baseline CPI plus a number of individual miss event CPI components. CPI stacks can be very helpful in gaining insight into the behavior of an application on a given microprocessor; consequently, they are widely used by software application developers and computer architects. However, computing CPI stacks on superscalar out-of-order processors is challenging because of various overlaps among execution and miss events (cache misses, TLB misses, and branch mispredictions).This paper shows that meaningful and accurate CPI stacks can be computed for superscalar out-of-order processors. Using interval analysis, a novel method for analyzing out-of-order processor performance, we gain understanding into the performance impact of the various miss events. Based on this understanding, we propose a novel way of architecting hardware performance counters for building accurate CPI stacks. The additional hardware for implementing these counters is limited and comparable to existing hardware performance counter architectures while being significantly more accurate than previous approaches.

A performance counter architecture for computing accurate CPI components

Ultrahigh storage densities can be achieved by using a thermomechanical scanning-probe-based data-storage approach to write, read back, and erase data in very thin polymer films. High data rates are achieved by parallel operation of large two-dimensional arrays of cantilevers that can be batch fabricated by silicon-surface micromachining techniques. The very high precision required to navigate the storage medium relative to the array of probes is achieved by microelectromechanical system (MEMS)- based x and y actuators. The ultrahigh storage densities offered by probe-storage devices pose a significant challenge in terms of both control design for nanoscale positioning and read-channel design for reliable signal detection. Moreover, the high parallelism necessitates new dataflow architectures to ensure high performance and reliability of the system. In this paper, we present a small-scale prototype system of a storage device that we built based on scanning-probe technology. Experimental results of multiple sectors, recorded using multiple levers at 840 Gb/in2 and read back without errors, demonstrate the functionality of the prototype system. This is the first time a scanning-probe recording technology has reached this level of technical maturity, demonstrating the joint operation of all building blocks of a storage device.

Probe-based ultrahigh-density storage technology

Bluetooth Low Energy (BLE) and the iBeacons have recently gained large interest for enabling various proximity-based application services. Given the ubiquitously deployed nature of Bluetooth devices including mobile smartphones, using BLE and iBeacon technologies seemed to be a promising future to come. This work started off with the belief that this was true: iBeacons could provide us with the accuracy in proximity and distance estimation to enable and simplify the development of many previously difficult applications. However, our empirical studies with three different iBeacon devices from various vendors and two types of smartphone platforms prove that this is not the case. Signal strength readings vary significantly over different iBeacon vendors, mobile platforms, environmental or deployment factors, and usage scenarios. This variability in signal strength naturally complicates the process of extracting an accurate location/proximity estimation in real environments. Our lessons on the limitations of iBeacon technique lead us to design a simple class attendance checking application by performing a simple form of geometric adjustments to compensate for the natural variations in beacon signal strength readings. We believe that the negative observations made in this work can provide future researchers with a reference on how well of a performance to expect from iBeacon devices as they enter their system design phases.

/pdf/a-measurement-study-of-ble-ibeacon-and-geometric-adjustment-lwqb1tzb5v.pdf

A Measurement Study of BLE iBeacon and Geometric Adjustment Scheme for Indoor Location-Based Mobile Applications

Despite years of study, branch mispredictions remain as a significant performance impediment in pipelined superscalar processors. In general, the branch misprediction penalty can be substantially larger than the frontend pipeline length (which is often equated with the misprediction penalty). We identify and quantify five contributors to the branch misprediction penalty: (i) the frontend pipeline length, (ii) the number of instructions since the last miss event (branch misprediction, I-cache miss, long D-cache miss)-this is related to the burstiness of miss events, (iii) the inherent ILP of the program, (iv) the functional unit latencies, and (v) the number of short (LI) D-cache misses. The characterizations done in this paper are driven by 'interval analysis', an analytical approach that models superscalar processor performance as a sequence of inter-miss intervals.

/pdf/characterizing-the-branch-misprediction-penalty-4ychihlejt.pdf

Characterizing the branch misprediction penalty

Bluetooth Low Energy (BLE) is a newly emerged technology targeting low-power, low-cost wireless communications within medium or short range. BLE has extended the already wide acceptance of Bluetooth and is an ideal choice for a variety of sensor-based products, as well as ubiquitous mobile devices. Recently, it has been proposed that indoor positioning can be achieved when scattering BLE sensor devices, called iBeacons, in various locations of a particular venue. In this work, we present an Android-based application for analyzing iBeacon networks and determining the best signal map. We also demonstrate the application of the presented analyzer for measuring the radiation pattern of iBeacon devices.

A bluetooth smart analyzer in iBeacon networks

In this paper we describe the methodology and architectureof a flexible modular environment for prototypingdata transmission systems and its application on xDSL systems.The development environment is based on custom andcommercially available software tools and a custom hardwareemulation platform for mapping the basic data-pumpmodules of xDSL systems into hardware/software functionalmodules. The road-map from a high-level xDSL systemmodel to the actual prototype is based on the progressivesubstitution of high-level submodules of the initial modelwith their respective hardware/software counterparts, andtheir integration into a complete functional system. A libraryof custom blocks is used for data exchange and synchronizationbetween the high-level model and the emulationplatform, and for real-time visualization of the criticalparameters of the emulated system as well. The applicationof the proposed development environment in the implementationand testing of an emulator of a bundle of DSL linesand of a centralized bit-loading algorithm for multicarrierADSL systems is also described.

An Instruction Throughput Model of Superscalar Processors

We present a new data allocation method for probe-based storage devices that use multiple, simultaneously accessed parallel data fields. Our method uses blocks of data of unequal length for allocating a sector in the various storage fields. The amount of data stored in each field depends on the sector's offset from the beginning of the allocation round and on the storage field used. Numerical results demonstrate the storage efficiency improvement that is achieved by the proposed method. We show that this method can be applied to atomic force microscopy-based probe storage devices.

/pdf/a-new-data-allocation-method-for-parallel-probe-based-49nxabg8qc.pdf

A New Data Allocation Method for Parallel Probe-Based Storage Devices

In this paper we describe an efficient methodology for rapid prototyping of data transmission systems based on Stateflow/Simulink models using a multi-level system development and testing approach. Transmission systems incorporate multi-domain functions and algorithms, i.e. physical layer circuits and communication protocol controllers. The Stateflow/Simulink environment enables the development of precise simulation models that include signal and protocol processing units. The proposed prototyping methodology is based on the progressive translation of high-level model blocks into hardware/software modules of the prototype architecture using custom and/or automated code generation tools. A custom data exchange and synchronization interface between the Stateflow/Simulink workspace and the circuit modules enables the integration of the simulation model and the prototyping platform into a complete functional system. The application of the proposed methodology in the development of an ADSL modem in a custom prototyping platform is also described.

Transmission systems prototyping based on Stateflow/Simulink models

Apache Spark is a popular open-source framework for distributed execution of data analytics and machine learning tasks, but with limited support for neural networks. In this work, we investigate the reasons for that and based on our findings we extend the native MLLib library with Restricted Boltzmann Machines, a common building block of deep learning architectures, along with a gradient descent optimization procedure suitable for neural networks. As a case study, we developed a handwritten digit recognition application using discriminative RBMs to demonstrate the performance of our implementation.

Maria Varsamou

Papers

A bluetooth smart analyzer in iBeacon networks

An Instruction Throughput Model of Superscalar Processors

A New Data Allocation Method for Parallel Probe-Based Storage Devices

Transmission systems prototyping based on Stateflow/Simulink models

Classification using Discriminative Restricted Boltzmann Machines on Spark