.png){kind=icon}
.png){kind=icon}
Return
A Tag Based Random Order Vector Reduction Circuit
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2976764.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Vector reduction is a very common operation to reduce a vector into a single scalar value in many scientific and engineering application scenarios. Therefore a fast and efficient vector reduction circuit has great significance to the real-time system applications. Usually the pipeline structure is widely adopted to increase the throughput of the vector reduction circuit and achieve maximum efficiency. In this paper, to deal with multiple vectors of variable length in random input sequence, a novel tag based fully pipelined vector reduction circuit is firstly proposed, in which a cache state module is used to queer and update the cache state of each vector. However, when the quantity of the input vector becomes large, a larger cache state module is required, which consumes more combinational logic and lower the operating frequency. To solve this problem, a high speed circuit is proposed in which the input vectors will be divided into several groups and sent into the dedicated cache state circuits, which can improve the operating frequency. Compared with other existing work, the prototype circuit and the improved circuit based on the prototype circuit can achieve the smallest Slices xus (<80% of the state-of-the-art work) for different input vector lengths. Moreover, both circuits can provide simple and efficient interface whose access timing is similar to that of a RAM. Therefore the circuits can be applied in a greater range.
Keywords:
Pipelines
Hardware
Clocks
Adders
Field programmable gate arrays
Binary trees
Out of order
Field-programmable gate arrays
fully pipelined
vector reduction
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.