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《International Journal of Parallel, Emergent and Distributed Systems》2012,27(3):227-248
Abstract This paper presents a method for parallelising nested loops with affine dependences. The data dependences of a program are represented exactly using a dependence matrix rather than an imprecise dependence abstraction. By a careful analysis of the eigenvectors and eigenvalues of the dependence matrix, we detect the parallelism inherent in the program, partition the iteration space of the program into sequential and parallel regions, and generate parallel code to execute these regions. For a class of programs considered in the paper, the proposed method can expose more coarse-grain and fine-grain parallelism than a hyperplane-based loop transformation. 相似文献
3.
Paul Feautrier 《International journal of parallel programming》1992,21(6):389-420
This paper extends the algorithms which were developed in Part I to cases in which there is no affine schedule, i.e. to problems whose parallel complexity is polynomial but not linear. The natural generalization is to multidimensional schedules with lexicographic ordering as temporal succession. Multidimensional affine schedules, are, in a sense, equivalent to polynomial schedules, and are much easier to handle automatically. Furthermore, there is a strong connection between multidimensional schedules and loop nests, which allows one to prove that a static control program always has a multidimensional schedule. Roughly, a larger dimension indicates less parallelism. In the algorithm which is presented here, this dimension is computed dynamically, and is just sufficient for scheduling the source program. The algorithm lends itself to a divide and conquer strategy. The paper gives some experimental evidence for the applicability, performances and limitations of the algorithm. 相似文献
4.
A recently proposed pipelined multithreading (PMT) technique exhibits wide applicability in parallelizing general sequential programs on multi-core processors. However, significant inter-core communication overhead limits PMT performance and prevents its commercial utilization. A simple and effective clustered pipelined multithreading (CPMT) approach is presented to accelerate sequential programs on commodity multi-core processors. This CPMT technique adopts a clustered communication mechanism that can yield very low average communication overhead by eliminating false sharing as well as reducing communication operation and transit delays in the software-only approach. A single-producer/single-consumer concurrent lock-free clusteredQueue algorithm based on a two-level queue structure is also proposed. The accuracy of CPMT is theoretically demonstrated. The performances of the algorithm and CPMT are evaluated on a commodity AMD Phenom four-core processor. The number of enqueue and dequeue times of the algorithm are 20.8 and 23 cycles given an appropriate parameter, respectively. The speedup of CPMT ranges from 13.1% to 119.8% for typical loops extracted from the SPEC CPU 2000 benchmark suite. 相似文献
5.
《Journal of Parallel and Distributed Computing》2014,74(12):3202-3216
The manycore revolution can be characterized by increasing thread counts, decreasing memory per thread, and diversity of continually evolving manycore architectures. High performance computing (HPC) applications and libraries must exploit increasingly finer levels of parallelism within their codes to sustain scalability on these devices. A major obstacle to performance portability is the diverse and conflicting set of constraints on memory access patterns across devices. Contemporary portable programming models address manycore parallelism (e.g., OpenMP, OpenACC, OpenCL) but fail to address memory access patterns. The Kokkos C++ library enables applications and domain libraries to achieve performance portability on diverse manycore architectures by unifying abstractions for both fine-grain data parallelism and memory access patterns. In this paper we describe Kokkos’ abstractions, summarize its application programmer interface (API), present performance results for unit-test kernels and mini-applications, and outline an incremental strategy for migrating legacy C++ codes to Kokkos. The Kokkos library is under active research and development to incorporate capabilities from new generations of manycore architectures, and to address a growing list of applications and domain libraries. 相似文献
6.
We studied the architecture of embedded computing systems from the viewpoint of power consumption in memory systems and used a selective-code-compression (SCC) approach to realize our design.Based on t... 相似文献
7.
Haoqiang Jin Barbara Chapman Lei Huang Dieter an Mey Thomas Reichstein 《International journal of parallel programming》2008,36(3):312-325
We describe a performance study of a multi-zone application benchmark implemented in several OpenMP approaches that exploit
multi-level parallelism and deal with unbalanced workload. The multi-zone application was derived from the well-known NAS
Parallel Benchmarks (NPB) suite that involves flow solvers on collections of loosely coupled discretization meshes. Parallel
versions of this application have been developed using the Subteam concept and Workqueuing model as extensions to the current
OpenMP. We examine the performance impact of these extensions to OpenMP and compare with hybrid and nested OpenMP approaches
on several large parallel systems. 相似文献
8.
基于并列选择遗传算法的多机器人协作探测 总被引:1,自引:0,他引:1
多机器人系统在执行探测任务时,存在多个机器人同时选择相同探测区域而造成碰撞几率增加和探测效率降低的问题.在原有并列选择遗传算法的基础上,提出了一种改进的遗传算法.仿真和实验结果表明,将该算法应用于多机器人协作区域探测,可以减小机器人之间的碰撞几率,提高多机器人系统的探测效率. 相似文献
9.
S. D. Pogorilyy Yu. V. Boyko A. D. Gusarov S. I. Lozytskyi 《Cybernetics and Systems Analysis》2009,45(2):291-296
The body of mathematics of modified systems of algorithmic algebras (SAA-M) is used to formalize the Edmonds–Karp algorithm
of finding the maximum flow in a network. With allowance made for the distributed system features that are usually used for
solving complicated problems, optimization criteria are formulated and used to obtain parallel SAA-M-schemes.
Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 146–152, March–April 2009. 相似文献
10.
Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related
death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural
and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses
(CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in complex tissue.
The first step toward the creation of such CADx tools requires mechanisms for automatically learning to classify tissue types—a
key step on the diagnosis process. Here we demonstrate that genetics-based machine learning (GBML) can be used to approach
such a problem. However, to efficiently analyze this problem there is a need to develop efficient and scalable GBML implementations
that are able to process very large data sets. In this paper, we propose and validate an efficient GBML technique——based on an incremental genetics-based rule learner. exploits massive parallelisms via the message passing interface (MPI) and efficient rule-matching using hardware-implemented
operations. Results demonstrate that is capable of performing prostate tissue classification efficiently, making a compelling case for using GBML implementations
as efficient and powerful tools for biomedical image processing. 相似文献