A fast, streaming SIMD extensions 2, logistic squashing function

Schraudolph proposed an excellent exponential approximation providing increased performance particularly suited to the logistic squashing function used within many neural networking applications. This note applies Intel's streaming SIMD Extensions 2 (SSE2), where SIMD is single instruction multiple data, of the Pentum IV class processor to Schraudolph's technique, further increasing the performance of the logistic squashing function. It was found that the calculation of the new 32-bit SSE2 logistic squashing function described here was up to 38 times faster than the conventional exponential function and up to 16 times faster than a Schraudolph-style 32-bit method on an Intel Pentum D 3.6 GHz CPU.

A parallel computation of power system equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and P4 classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

SSE based parallel solution for power systems network equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

A parallel solution to linear systems

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving linear systems with SSE and discuss advantages and disadvantages of this approach based on our experimental study.

Teaching parallel computing concepts with a desktop computer

Parallel computing is currently used in many engineering problems. However, because of limitations in curriculum design, it is not always possible to offer students specific formal teaching in this topic. Furthermore, parallel machines are still too expensive for many institutions. The latest microprocessors, such as Intel’s Pentium III and IV, embody single instruction multiple-data (SIMD) type parallel features, which makes them a viable solution for introducing parallel computing concepts to students. Final year projects have been initiated utilizing SSE (streaming SIMD extensions) features and it has been observed that students can easily learn parallel programming concepts after going through some programming exercises. They can now experiment with parallel algorithms on their own PCs at home. Keywords

Parallel linear system solution and its application to railway power network simulation

The Streaming SIMD extension (SSE) is a special feature embedded in the Intel Pentium III and IV classes of microprocessors. It enables the execution of SIMD type operations to exploit data parallelism. This article presents improving computation performance of a railway network simulator by means of SSE. Voltage and current at various points of the supply system to an electrified railway line are crucial for design, daily operation and planning. With computer simulation, their time-variations can be attained by solving a matrix equation, whose size mainly depends upon the number of trains present in the system. A large coefficient matrix, as a result of congested railway line, inevitably leads to heavier computational demand and hence jeopardizes the simulation speed. With the special architectural features of the latest processors on PC platforms, significant speed-up in computations can be achieved.

Parallel solution for railway power network simulation

The Streaming SIMD extension (SSE) is a special feature that is available in the Intel Pentium III and P4 classes of microprocessors. As its name implies, SSE enables the execution of SIMD (Single Instruction Multiple Data) operations upon 32-bit floating-point data therefore, performance of floating-point algorithms can be improved. In electrified railway system simulation, the computation involves the solving of a huge set of simultaneous linear equations, which represent the electrical characteristic of the railway network at a particular time-step and a fast solution for the equations is desirable in order to simulate the system in real-time. In this paper, we present how SSE is being applied to the railway network simulation.

A framework for post-silicon realization of arbitrary instruction extensions on reconfigurable data-paths

In this paper we present a framework for realizing arbitrary instruction set extensions (IE) that are identified post-silicon. The proposed framework has two components viz., an IE synthesis methodology and the architecture of a reconfigurable data-path for realization of the such IEs. The IE synthesis methodology ensures maximal utilization of resources on the reconfigurable data-path. In this context we present the techniques used to realize IEs for applications that demand high throughput or those that must process data streams. The reconfigurable hardware called HyperCell comprises a reconfigurable execution fabric. The fabric is a collection of interconnected compute units. A typical use case of HyperCell is where it acts as a co-processor with a host and accelerates execution of IEs that are defined post-silicon. We demonstrate the effectiveness of our approach by evaluating the performance of some well-known integer kernels that are realized as IEs on HyperCell. Our methodology for realizing IEs through HyperCells permits overlapping of potentially all memory transactions with computations. We show significant improvement in performance for streaming applications over general purpose processor based solutions, by fully pipelining the data-path. (C) 2014 Elsevier B.V. All rights reserved.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

The effect of brand extensions on parent-brand relationship quality

A recognized brand name that provides a competitive advantage is considered one of a firm’s most valuable assets. Many firms have benefitted from their well-established brand name by adopting the strategy of brand extension (Aaker and Keller, 1990). Many academic studies have examined the methods used to introduce successful brand extensions, and analysed how consumers evaluate the brand extensions (Aaker and Keller, 1990; Barone, 2005; Bath, 1997; Bottomley and Holden, 2001; Edelman, 2003; Fedorikhin, Park and Thomson, 2008; Kwun, 2004; Lockhart and Ford, 2005). Some researchers have suggested that brand extension strategies may carry the risk of diluting important consumer trust in the parent brand (Martinez and Pina, 2003; C. W. Park, Milberg and Lawson, 1991). Furthermore, some studies have focused on the role of the parent brand in brand extensions (Apostolopoulou, 2002; Bath, 1997; Bhat and Reddy, 2001; Yeung and Wyer Jr, 2005). Brand extensions may have a positive or a negative influence on the parent brand, so it is important to understand the specific impact on dimensions such as brand image, brand awareness, and customer-brand relationships. This study will carry investigate the effects of brand extensions on the relationships customers have with the parent brand.

Real-time image streaming over a low-bandwidth wireless camera network

In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. © 2007 IEEE.

Poster Abstract : A sensor network for compression and streaming of GPS trajectory data

We present the design and deployment results for PosNet - a large-scale, long-duration sensor network that gathers summary position and status information from mobile nodes. The mobile nodes have a fixed-sized memory buffer to which position data is added at a constant rate, and from which data is downloaded at a non-constant rate. We have developed a novel algorithm that performs online summarization of position data within the buffer, where the algorithm naturally accommodates data input and output rate mismatch, and also provides a delay-tolerant approach to data transport. The algorithm has been extensively tested in a large-scale long-duration cattle monitoring and control application.

ERTP : Energy-efficient and reliable transport protocol for data streaming in wireless sensor networks

Emerging data streaming applications in Wireless Sensor Networks require reliable and energy-efficient Transport Protocols. Our recent Wireless Sensor Network deployment in the Burdekin delta, Australia, for water monitoring [T. Le Dinh, W. Hu, P. Sikka, P. Corke, L. Overs, S. Brosnan, Design and deployment of a remote robust sensor network: experiences from an outdoor water quality monitoring network, in: Second IEEE Workshop on Practical Issues in Building Sensor Network Applications (SenseApp 2007), Dublin, Ireland, 2007] is one such example. This application involves streaming sensed data such as pressure, water flow rate, and salinity periodically from many scattered sensors to the sink node which in turn relays them via an IP network to a remote site for archiving, processing, and presentation. While latency is not a primary concern in this class of application (the sampling rate is usually in terms of minutes or hours), energy-efficiency is. Continuous long-term operation and reliable delivery of the sensed data to the sink are also desirable. This paper proposes ERTP, an Energy-efficient and Reliable Transport Protocol for Wireless Sensor Networks. ERTP is designed for data streaming applications, in which sensor readings are transmitted from one or more sensor sources to a base station (or sink). ERTP uses a statistical reliability metric which ensures the number of data packets delivered to the sink exceeds the defined threshold. Our extensive discrete event simulations and experimental evaluations show that ERTP is significantly more energyefficient than current approaches and can reduce energy consumption by more than 45% when compared to current approaches. Consequently, sensor nodes are more energy-efficient and the lifespan of the unattended WSN is increased.