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Pipeline (computing)

About: Pipeline (computing) is a research topic. Over the lifetime, 26760 publications have been published within this topic receiving 204305 citations. The topic is also known as: data pipeline & computational pipeline.


Papers
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Journal ArticleDOI
TL;DR: An energy profiler tool for the systems that use ARM7TDMI processors is developed by embedding the model parameters in an instruction-level profiler from the SimpleScalar toolset which provides valuable information and guidelines for software energy optimization.
Abstract: Estimating the energy consumption of applications is a key aspect in optimizing embedded systems energy consumption. This paper proposes a simple yet accurate instruction-level energy estimation model for embedded systems. As a case study, the model parameters were determined for a commonly used ARM7TDMI-based microcontroller. The total energy includes the energy consumption of the processor core, Flash memory, memory controller, and SRAM. The model parameters are instructions opcode, number of shift operations, register bank bit flips, instructions weight and their Hamming distance, and different types of memory accesses. Also, the effect of pipeline stalls have been considered. In order to validate the proposed model, a physical hardware platform equipped with energy measurement capabilities was developed. We have conducted experiments on several embedded applications from MiBench benchmark suite and the results show less than 6% error in the energy consumption estimation. We have also developed an energy profiler tool for the systems that use ARM7TDMI processors by embedding the model parameters in an instruction-level profiler from the SimpleScalar toolset which provides valuable information and guidelines for software energy optimization.

71 citations

Journal ArticleDOI
TL;DR: In this paper, the dynamics of a pipeline conveying one-dimensional unsteady flow is considered, which is represented by a set of partial differential equations which consists of the axial and transverse equations of motion of the pipeline and the equations of momentum and continuity of the internal flow.

71 citations

Book ChapterDOI
01 Jan 1981
TL;DR: A two-level pipelined systolic array that is capable of performing convolutions of any dimension and the designs take full advantages of the pipelining assumed to be available at each cell are described.
Abstract: Pipelining computations over a large array of cells has been an important feature of systolic arrays. To achieve even higher degrees of concurrency, it is desirable to have cells of a systolic array themselves be pipelined as well. The resulting two-level pipelined systolic array would enjoy in principle a k-fold increase in its throughput, where k is the ratio of the time to perform the entire cell computation over that to perform just one of its pipeline stages. This paper describes such a two-level pipelined systolic array that is capable of performing convolutions of any dimension. The designs take full advantages of the pipelining assumed to be available at each cell.

71 citations

Patent
Joerg Schepers1
01 Mar 1994
TL;DR: In this article, a heuristic selection process is used to select the instructions whose precursor instructions have already been processed and investigate these instructions as to whether before their execution a minimum number of delay cycles is necessary.
Abstract: In order to be able to execute rapid processing of a program on super-scalar microprocessors, the individual instructions of this program must be divided into instruction groups, which can be processed by processing units of the microprocessor, in such a way that the instructions can be processed in parallel. In this case, it is necessary to take account of data-flow dependences and control-flow dependences as well as pipeline conflicts. For this purpose, the first step is to select the instructions whose precursor instructions have already been processed and to investigate these instructions as to whether before their execution a minimum number of delay cycles is necessary, and the instructions are stored with a minimum number in a list. From these instructions, one is selected using a heuristic selection process, and this one is classified into an instruction group in which the instruction can be processed in the earliest possible execution cycle.

71 citations

Journal ArticleDOI
TL;DR: Measurements of the sensitivity of the pipeline used to generate the Q1-Q17 DR24 planet candidate catalog find a strong period dependence in the measured detection efficiency, with longer (>40 day) periods having a significantly lower detectability than shorter periods.
Abstract: With each new version of the Kepler pipeline and resulting planet candidate catalog, an updated measurement of the underlying planet population can only be recovered with a corresponding measurement of the Kepler pipeline detection efficiency. Here we present measurements of the sensitivity of the pipeline (version 9.2) used to generate the Q1–Q17 DR24 planet candidate catalog. We measure this by injecting simulated transiting planets into the pixel-level data of 159,013 targets across the entire Kepler focal plane, and examining the recovery rate. Unlike previous versions of the Kepler pipeline, we find a strong period dependence in the measured detection efficiency, with longer (>40 day) periods having a significantly lower detectability than shorter periods, introduced in part by an incorrectly implemented veto. Consequently, the sensitivity of the 9.2 pipeline cannot be cast as a simple one-dimensional function of the signal strength of the candidate planet signal, as was possible for previous versions of the pipeline. We report on the implications for occurrence rate calculations based on the Q1–Q17 DR24 planet candidate catalog, and offer important caveats and recommendations for performing such calculations. As before, we make available the entire table of injected planet parameters and whether they were recovered by the pipeline, enabling readers to derive the pipeline detection sensitivity in the planet and/or stellar parameter space of their choice.

70 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202218
20211,066
20201,556
20191,793
20181,754
20171,548