Graphics processing units(GPUs) provide a low cost platform for accelerating high performance computations. New programming languages, such as CUDA and OpenCL, make GPU programming attractive to programmers. However, ...
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ISBN:
(纸本)9781479961238
Graphics processing units(GPUs) provide a low cost platform for accelerating high performance computations. New programming languages, such as CUDA and OpenCL, make GPU programming attractive to programmers. However, programming GPUs is still a cumbersome task for two reasons, tedious performance optimizations and lack of portability. First, optimizing an algorithm for a specific GPU is a time-consuming task that requires a thorough understanding of boththe algorithm and the underlying hardware. Unoptimized CUDA programs typically only achieve a small fraction of the peak GPU performance. Second, CUDA programs lack performance portability between different GPUs. Moving code from one GPU to another while maintaining the desired performance is a non-trivial task which often requires significant time. In this paper, we propose an optimized compiler that compiles a representative high level directive-based language to CUDA, which is capable of performing a wide variety of optimizations to generate efficient code for GPUs. We alleviate the portability problem of current GPU programming methods by using a high level directive-based language that provides a unified abstraction for currently popular CPU-GPU heterogeneous systems. Various optimizations, mainly the memory system optimizations, are automatically applied by our compiler to produce optimized CUDA code for GPU. Experiments on rodinia benchmark with different input sizes shows that our compiler achieves 70%, 75%, 84% performance of hand-written code on average respectively.
the problems of determining open locating-dominating or locating total-dominating sets of minimum cardinality in a graph G are variations of the classical minimum dominating set problem in G and are all known to be ha...
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ISBN:
(纸本)9783030532611;9783030532628
the problems of determining open locating-dominating or locating total-dominating sets of minimum cardinality in a graph G are variations of the classical minimum dominating set problem in G and are all known to be hard for general graphs. A typical line of attack is therefore to determine the cardinality of minimum such sets in special graphs. In this work we study the two problems from a polyhedral point of view. We provide the according linear relaxations, discuss their combinatorial structure, and demonstrate how the associated polyhedra can be entirely described or polyhedral arguments can be applied to find minimum such sets for special graphs.
three-dimensional distribution calculations are performed for the ITER-FEAT vacuum vessel (VV), the connected pressure suppression pool (SP) and drain tank (DT). A first-wall coolant leak without plasma shutdown is si...
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three-dimensional distribution calculations are performed for the ITER-FEAT vacuum vessel (VV), the connected pressure suppression pool (SP) and drain tank (DT). A first-wall coolant leak without plasma shutdown is simulated. the steam, hydrogen, and air sources for this sequence are taken from best-estimate MELCOR calculations. A new extended version Of GASFLOW is used to model the ITER-FEAT specific phenomena in adequate detail. During the accident sequence, hydrogen initially appears only in the VV due to the steam/beryllium reaction. After opening of the valves, steam and hydrogen flow from the W through the connecting lines to the SP and the DT. Because of the ongoing steam condensation occurring in the SP, the pressure there remains permanently at a lower level compared to the other components, resulting in a continuous flow of steam and noncondensable gases into this volume. After 10 500s of steam flow, also air starts entering the W, and an accumulation of N(2) and O(2) takes place in the SP cover gas. Combustible and explosive H(2)-O(2)-N(2) Mixtures exist after 13 600 s, and at 21000 s a stoichiometric H(2)/O(2) ratio has formed, involving 13 kg of hydrogen. (C) 2002 Elsevier Science B.V. All rights reserved.
Reconfigurable Intelligent Surface (RIS) is one of the key technologies for the upcoming 6thgeneration (6G) communications, which can improve the signal strength at the receivers by adding artificial propagation path...
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this paper investigates the design of a linear minimum mean square error (MMSE) receiver for interference suppression in asynchronous random code-division multiple-access (Random-CDMA) systems, such as IS-95 and Wideb...
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this paper investigates the design of a linear minimum mean square error (MMSE) receiver for interference suppression in asynchronous random code-division multiple-access (Random-CDMA) systems, such as IS-95 and Wideband-CDMA (WCDMA), operating in multipath environments. Its performance is compared withthat of the coherent RAKE receiver. the figure of merit is average output signal-to-noise-ratio (SNR). the proposed receiver maximizes SNR and considers all the desired user's paths unlike the standard RAKE receiver which selects a subset of them. the performance improvement is supported and quantified by numerical examples. the achieved gain is shown to be substantial in non-uniform power conditions (typical of next-generation CDMA systems) and dense multipath environments where the signals are received via many paths. the chip pulse shape is the square-root raised cosine (Sqrt-RC) pulse with 22% excess bandwidth.
this paper presents an alternative technique to improve the gain tuning of nonlinear backstepping controller applied to three-phase grid-connected photovoltaic (PV) system in order to control active and reactive power...
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ISBN:
(纸本)9781665419178
this paper presents an alternative technique to improve the gain tuning of nonlinear backstepping controller applied to three-phase grid-connected photovoltaic (PV) system in order to control active and reactive power fed into the grid. Gain parameters of nonlinear backstepping controllers play a key role in the convergence of currents corresponding to active and reactive power in grid-connected PV systems. the use of Differential Evolution (DE) optimization technique is proposed in this work, to obtain the optimised gain parameters while ensuring the fast convergence of errors associated with currents and this is done by minimizing the fitness function. Meanwhile, the gains are also optimised using an effective DE variant, differential evolution with composite trial vector generation strategies and control parameters (code). the control parameter selection plays a vital role in the efficient performance of DE algorithm. However, the best choice of control parameters for optimum performance varies from problem to problem. Simulation studies are carried out to validate the effectiveness of the proposed scheme in terms of time responses (e.g., rise time, settling time, peak time, etc.)
作者:
Dries, AntonKU Leuven
Dept. of Computer Science Celestijnenlaan 200A - bus 2402 Heverlee3001 Belgium
In this paper we describe a novel declarative approach to data generation based on probabilistic logic programming. We show that many data generation tasks can be described as a probabilistic logic program. To this en...
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this article proposes approaches supporting the analysis of code vulnerabilities based on overlapping machine instructions of variable length. For the purpose of focusing the search for potential malicious code it is ...
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the proceedings contain 39 papers. the topics discussed include: efficient and effective neural networks for automatic test pattern generation;learning to compare hardware designs for high-level synthesis;FACT: fast a...
ISBN:
(纸本)9798400706998
the proceedings contain 39 papers. the topics discussed include: efficient and effective neural networks for automatic test pattern generation;learning to compare hardware designs for high-level synthesis;FACT: fast and accurate multi-corner predictor for timing closure in commercial EDA flows;enhancing the capabilities of quantum transport simulations utilizing machine learning strategies;AnML-aided approach to automatically generate schematic symbols in PCB EDA tools;IR-aware ECO timing optimization using reinforcement learning;a parallel simulation framework incorporating machine learning-based hotspot detection for accelerated power grid analysis;flip-flop centric incremental placement for simultaneous timing and clock network power optimization;and automated physical design watermarking leveraging graph neural network.
Unique word (UW-) OFDM is a novel multicarrier system that is shown to be suitable for cognitive radio systems. To construct the UW-OFDM signal, a codegeneration matrix is required to introduce redundancy in the freq...
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Unique word (UW-) OFDM is a novel multicarrier system that is shown to be suitable for cognitive radio systems. To construct the UW-OFDM signal, a codegeneration matrix is required to introduce redundancy in the frequency domain, implying that the codegeneration matrix must satisfy a number of conditions. In this paper, we use an algebraic construction method to separate the conditions imposed by the signal shape from the code design. the degrees of freedom resulting from this construction method are used to optimize different performance measures (i.e., the minimum Euclidean distance and the power) at the transmitter or at the receiver side. Based on the algebraic decomposition, a composite channel can be defined. Irrespective of whether the optimization is done at the transmitter or the receiver, we shown in the paper that always the strongest modes of this composite channel must be excited.
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