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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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Proceedings ArticleDOI
11 May 1998
TL;DR: By exploiting the spatial regularity of the new algorithm, minimal requirement for both dominant components in VLSI implementation has been achieved: only 4 complex multipliers and 1024 complex-word data memory for the pipelined 1K FFT processor.
Abstract: The design and implementation of a 1024-point pipeline FFT processor is presented. The architecture is based on a new form of FFT, the radix-2/sup 2/ algorithm. By exploiting the spatial regularity of the new algorithm, minimal requirement for both dominant components in VLSI implementation has been achieved: only 4 complex multipliers and 1024 complex-word data memory for the pipelined 1K FFT processor. The chip has been implement in 0.5 /spl mu/m CMOS technology and takes an area of 40 mm/sup 2/. With 3.3 V power supply, it can compute 2/sup n/, n=0, 1, ..., 10 complex point forward and inverse FFT in real time with up to 30 MHz sampling frequency. The SQNR is above 50 dB for white noise input.

243 citations

Journal ArticleDOI
TL;DR: In this article, a brief overview of the INT Wide Field Camera (WFC) together with the automated pipeline processing developed specifically for the Wide Field Survey (WFS) is presented.

241 citations

Journal ArticleDOI
Byung-Moo Min1, P. Kim1, F.W. Bowman, D.M. Boisvert, A.J. Aude 
TL;DR: The proposed feedback signal polarity inverting (FSPI) technique addresses the drawback of the conventional amplifier sharing technique and helps to reduce power consumption in a 10-bit pipeline.
Abstract: A 10-bit 80-MS/s analog-to-digital converter (ADC) with an area- and power-efficient architecture is described. By sharing an amplifier between two successive pipeline stages, a 10-bit pipeline is realized using just four amplifiers with a separate sample-and-hold block. The proposed feedback signal polarity inverting (FSPI) technique addresses the drawback of the conventional amplifier sharing technique. A wide-swing wide-bandwidth telescopic amplifier and an early comparison technique with a constant delay circuit have been developed to further reduce power consumption. The ADC is implemented in a 0.18-/spl mu/m dual-gate-oxidation CMOS process technology, achieves 72.8-dBc spurious free dynamic range, 57.92-dBc signal-to-noise ratio, 9.29 effective number of bits (ENOB) for a 99-MHz input at full sampling rate, and consumes 69 mW from a 3-V supply. The ADC occupies 1.85 mm/sup 2/.

234 citations

Proceedings ArticleDOI
01 Apr 2017
TL;DR: This paper proposes a novel architecture for implementing Winograd algorithm on FPGAs and proposes an analytical model to predict the resource usage and reason about the performance, and uses the model to guide a fast design space exploration.
Abstract: In recent years, Convolutional Neural Networks (CNNs) have become widely adopted for computer vision tasks. FPGAs have been adequately explored as a promising hardware accelerator for CNNs due to its high performance, energy efficiency, and reconfigurability. However, prior FPGA solutions based on the conventional convolutional algorithm is often bounded by the computational capability of FPGAs (e.g., the number of DSPs). In this paper, we demonstrate that fast Winograd algorithm can dramatically reduce the arithmetic complexity, and improve the performance of CNNs on FPGAs. We first propose a novel architecture for implementing Winograd algorithm on FPGAs. Our design employs line buffer structure to effectively reuse the feature map data among different tiles. We also effectively pipeline the Winograd PE engine and initiate multiple PEs through parallelization. Meanwhile, there exists a complex design space to explore. We propose an analytical model to predict the resource usage and reason about the performance. Then, we use the model to guide a fast design space exploration. Experiments using the state-of-the-art CNNs demonstrate the best performance and energy efficiency on FPGAs. We achieve an average 1006.4 GOP/s for the convolutional layers and 854.6 GOP/s for the overall AlexNet and an average 3044.7 GOP/s for the convolutional layers and 2940.7 GOP/s for the overall VGG16 on Xilinx ZCU102 platform.

233 citations

Patent
28 May 1996
TL;DR: The Adaptive Logic Processor (ALP) as mentioned in this paper uses a programmable logic structure called an adaptive logic processor, similar to an extendible field programmable gate array (FPGA) and is optimized for the implementation of program specific pipeline functions.
Abstract: An architecture for information processing devices which allows the construction of low cost, high performance systems for specialized computing applications involving sensor data processing. The reconfigurable processor architecture of the invention uses a programmable logic structure called an Adaptive Logic Processor (ALP). This structure is similar to an extendible field programmable gate array (FPGA) and is optimized for the implementation of program specific pipeline functions, where the function may be changed any number of times during the progress of a computation. A Reconfigurable Pipeline Instruction Control (RPIC) unit is used for loading the pipeline functions into the ALP during the configuration process and coordinating the operations of the ALP with other information processing structures, such as memory, I/O devices, and arithmetic processing units. Multiple components having the reconfigurable architecture of the present invention may be combined to produce high performance parallel processing systems based on the Single Instruction Multiple Data (SIMD) architecture concept.

232 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