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The training dataset for accelerated machine learning algorithms

Citation Author(s):
Submitted by:
Qi Yang
Last updated:
DOI:
10.21227/fbpn-s032
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Average: 5 (1 vote)

Abstract

A 128-dimensional vector for one document in text format, where each dimension is represented as a single precision floating-point number。

Instructions:

The training dataset was randomly generated for accelerated machine learning algorithms that the coputing-intensive tasks are offload to FPGA accelerators. And the data is stored as a 128-dimensional vector for one document in text format, where each dimension is represented as a single precision floating-point number, so that we can increase the size of dataset easily to hundreds of GB or even more. The cosine distance is used to measure the vector similarity.

 

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