Abstract: A real time distributed computing has
heterogeneously networked computers to solve a single problem. So
coordination of activities among computers is a complex task and
deadlines make more complex. The performances depend on many
factors such as traffic workloads, database system architecture,
underlying processors, disks speeds, etc. Simulation study have been
performed to analyze the performance under different transaction
scheduling: different workloads, arrival rate, priority policies,
altering slack factors and Preemptive Policy. The performance metric
of the experiments is missed percent that is the percentage of
transaction that the system is unable to complete. The throughput of
the system is depends on the arrival rate of transaction. The
performance can be enhanced with altering the slack factor value.
Working on slack value for the transaction can helps to avoid some
of transactions from killing or aborts. Under the Preemptive Policy,
many extra executions of new transactions can be carried out.
Abstract: System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.
Abstract: The intermittent connectivity modifies the “always
on" network assumption made by all the distributed query processing
systems. In modern- day systems, the absence of network
connectivity is considered as a fault. Since the last upload, it might
not be feasible to transmit all the data accumulated right away over
the available connection. It is possible that vital information may be
delayed excessively when the less important information takes place
of the vital information. Owing to the restricted and uneven
bandwidth, it is vital that the mobile nodes make the most
advantageous use of the connectivity when it arrives. Hence, in order
to select the data that needs to be transmitted first, some sort of data
prioritization is essential. A continuous query processing system for
intermittently connected mobile networks that comprises of a delaytolerant
continuous query processor distributed across the mobile
hosts has been proposed in this paper. In addition, a mechanism for
prioritizing query results has been designed that guarantees enhanced
accuracy and reduced delay. It is illustrated that our architecture
reduces the client power consumption, increases query efficiency by
the extensive simulation results.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: The H.264/AVC standard is a highly efficient video
codec providing high-quality videos at low bit-rates. As employing
advanced techniques, the computational complexity has been
increased. The complexity brings about the major problem in the
implementation of a real-time encoder and decoder. Parallelism is the
one of approaches which can be implemented by multi-core system.
We analyze macroblock-level parallelism which ensures the same bit
rate with high concurrency of processors. In order to reduce the
encoding time, dynamic data partition based on macroblock region is
proposed. The data partition has the advantages in load balancing and
data communication overhead. Using the data partition, the encoder
obtains more than 3.59x speed-up on a four-processor system. This
work can be applied to other multimedia processing applications.
Abstract: METIS is the Multi Element Telescope for Imaging
and Spectroscopy, a Coronagraph aboard the European Space
Agency-s Solar Orbiter Mission aimed at the observation of the solar
corona via both VIS and UV/EUV narrow-band imaging and spectroscopy. METIS, with its multi-wavelength capabilities, will
study in detail the physical processes responsible for the corona heating and the origin and properties of the slow and fast solar wind.
METIS electronics will collect and process scientific data thanks to its detectors proximity electronics, the digital front-end subsystem
electronics and the MPPU, the Main Power and Processing Unit,
hosting a space-qualified processor, memories and some rad-hard
FPGAs acting as digital controllers.This paper reports on the overall
METIS electronics architecture and data processing capabilities
conceived to address all the scientific issues as a trade-off solution between requirements and allocated resources, just before the
Preliminary Design Review as an ESA milestone in April 2012.
Abstract: This paper presents the benchmarking results and
performance evaluation of differentclustersbuilt atthe National Center
for High-Performance Computingin Taiwan. Performance of
processor, memory subsystem andinterconnect is a critical factor in the
overall performance of high performance computing platforms. The
evaluation compares different system architecture and software
platforms. Most supercomputer used HPL to benchmark their system
performance, in accordance with the requirement of the TOP500 List.
In this paper we consider system memory access factors that affect
benchmark performance, such as processor and memory
performance.We hope these works will provide useful information for
future development and construct cluster system.
Abstract: In this paper, low end Digital Signal Processors (DSPs)
are applied to accelerate integer neural networks. The use of DSPs
to accelerate neural networks has been a topic of study for some
time, and has demonstrated significant performance improvements.
Recently, work has been done on integer only neural networks, which
greatly reduces hardware requirements, and thus allows for cheaper
hardware implementation. DSPs with Arithmetic Logic Units (ALUs)
that support floating or fixed point arithmetic are generally more
expensive than their integer only counterparts due to increased circuit
complexity. However if the need for floating or fixed point math
operation can be removed, then simpler, lower cost DSPs can be
used. To achieve this, an integer only neural network is created in
this paper, which is then accelerated by using DSP instructions to
improve performance.
Abstract: We present a simplified equalization technique for a
π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated
signal in a multipath fading environment. The proposed equalizer is
realized as a fractionally spaced adaptive decision feedback equalizer
(FS-ADFE), employing exponential step-size least mean square
(LMS) algorithm as the adaptation technique. The main advantage of
the scheme stems from the usage of exponential step-size LMS algorithm
in the equalizer, which achieves similar convergence behavior
as that of a recursive least squares (RLS) algorithm with significantly
reduced computational complexity. To investigate the finite-precision
performance of the proposed equalizer along with the π/4 -DQPSK
modem, the entire system is evaluated on a 16-bit fixed point digital
signal processor (DSP) environment. The proposed scheme is found
to be attractive even for those cases where equalization is to be
performed within a restricted number of training samples.
Abstract: The deterministic quantum transfer-matrix (QTM)
technique and its mathematical background are presented. This
important tool in computational physics can be applied to a class of
the real physical low-dimensional magnetic systems described by the
Heisenberg hamiltonian which includes the macroscopic molecularbased
spin chains, small size magnetic clusters embedded in some
supramolecules and other interesting compounds. Using QTM, the
spin degrees of freedom are accurately taken into account, yielding
the thermodynamical functions at finite temperatures.
In order to test the application for the susceptibility calculations to
run in the parallel environment, the speed-up and efficiency of
parallelization are analyzed on our platform SGI Origin 3800 with
p = 128 processor units. Using Message Parallel Interface (MPI)
system libraries we find the efficiency of the code of 94% for
p = 128 that makes our application highly scalable.
Abstract: The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.
Abstract: In this paper, all-optical signal processors that perform
both microwave mixing and bandpass filtering in a radio-over-fiber
(RoF) link are presented. The key device is a Mach-Zehnder
modulator (MZM) which performs all-optical microwave mixing. An
up-converted microwave signal is obtained and other unwanted
frequency components are suppressed at the end of the fiber span.
Abstract: In this paper, we propose a novel concept of relative
distance measurement using Stereo Vision Technology and discuss
its implementation on a FPGA based real-time image processor. We
capture two images using two CCD cameras and compare them.
Disparity is calculated for each pixel using a real time dense disparity
calculation algorithm. This algorithm is based on the concept of
indexed histogram for matching. Disparity being inversely
proportional to distance (Proved Later), we can thus get the relative
distances of objects in front of the camera. The output is displayed on
a TV screen in the form of a depth image (optionally using pseudo
colors). This system works in real time on a full PAL frame rate (720
x 576 active pixels @ 25 fps).
Abstract: This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.
Abstract: We propose a novel prioritized limited
processor-sharing (PS) rule and a simulation algorithm for the performance evaluation of this rule. The performance measures of practical interest are evaluated using this algorithm. Suppose that there
are two classes and that an arriving (class-1 or class-2) request encounters n1 class-1 and n2 class-2 requests (including the arriving
one) in a single-server system. According to the proposed rule, class-1
requests individually and simultaneously receive m / (m * n1+ n2) of the service-facility capacity, whereas class-2 requests receive 1 / (m *n1 + n2) of it, if m * n1 + n2 ≤ C. Otherwise (m * n1 + n2 > C), the arriving request will be queued in the corresponding class waiting
room or rejected. Here, m (1) denotes the priority ratio, and C ( ∞), the service-facility capacity. In this rule, when a request arrives at [or
departs from] the system, the extension [shortening] of the remaining
sojourn time of each request receiving service can be calculated using
the number of requests of each class and the priority ratio. Employing
a simulation program to execute these events and calculations enables
us to analyze the performance of the proposed prioritized limited PS
rule, which is realistic in a time-sharing system (TSS) with a
sufficiently small time slot. Moreover, this simulation algorithm is
expanded for the evaluation of the prioritized limited PS system with
N 3 priority classes.
Abstract: Today-s Voltage Regulator Modules (VRMs) face increasing design challenges as the number of transistors in microprocessors increases per Moore-s Law. These challenges have recently become even more demanding as microprocessors operate at sub voltage range at significantly high current. This paper presents a new multiphase topology with cell configuration for improved performance in low voltage and high current applications. A lab scale hardware prototype of the new topology was design and constructed. Laboratory tests were performed on the proposed converter and compared with a commercially available VRM. Results from the proposed topology exhibit improved performance compared to the commercially available counterpart.
Abstract: One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Abstract: A new and highly efficient architecture for elliptic curve scalar point multiplication which is optimized for a binary field recommended by NIST and is well-suited for elliptic curve cryptographic (ECC) applications is presented. To achieve the maximum architectural and timing improvements we have reorganized and reordered the critical path of the Lopez-Dahab scalar point multiplication architecture such that logic structures are implemented in parallel and operations in the critical path are diverted to noncritical paths. With G=41, the proposed design is capable of performing a field multiplication over the extension field with degree 163 in 11.92 s with the maximum achievable frequency of 251 MHz on Xilinx Virtex-4 (XC4VLX200) while 22% of the chip area is occupied, where G is the digit size of the underlying digit-serial finite field multiplier.
Abstract: In a wireless communication system, a
predistorter(PD) is often employed to alleviate nonlinear distortions
due to operating a power amplifier near saturation, thereby improving
the system performance and reducing the interference to adjacent
channels. This paper presents a new adaptive polynomial digital
predistorter(DPD). The proposed DPD uses Coordinate Rotation
Digital Computing(CORDIC) processors and PD process by pipelined
architecture. It is simpler and faster than conventional adaptive
polynomial DPD. The performance of the proposed DPD is proved by
MATLAB simulation.
Abstract: All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.