Faster Base64 Encoding and Decoding Using AVX2 Instructions

Fuente: arXiv
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Autori principali: Muła, Wojciech, Lemire, Daniel
Natura: Preprint
Pubblicazione: 2017
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author Muła, Wojciech
Lemire, Daniel
author_facet Muła, Wojciech
Lemire, Daniel
contents Web developers use base64 formats to include images, fonts, sounds and other resources directly inside HTML, JavaScript, JSON and XML files. We estimate that billions of base64 messages are decoded every day. We are motivated to improve the efficiency of base64 encoding and decoding. Compared to state-of-the-art implementations, we multiply the speeds of both the encoding (~10x) and the decoding (~7x). We achieve these good results by using the single-instruction-multiple-data (SIMD) instructions available on recent Intel processors (AVX2). Our accelerated software abides by the specification and reports errors when encountering characters outside of the base64 set. It is available online as free software under a liberal license.
format Preprint
id arxiv_https___arxiv_org_abs_1704_00605
institution arXiv
publishDate 2017
record_format arxiv
spellingShingle Faster Base64 Encoding and Decoding Using AVX2 Instructions
Muła, Wojciech
Lemire, Daniel
Mathematical Software
Performance
Web developers use base64 formats to include images, fonts, sounds and other resources directly inside HTML, JavaScript, JSON and XML files. We estimate that billions of base64 messages are decoded every day. We are motivated to improve the efficiency of base64 encoding and decoding. Compared to state-of-the-art implementations, we multiply the speeds of both the encoding (~10x) and the decoding (~7x). We achieve these good results by using the single-instruction-multiple-data (SIMD) instructions available on recent Intel processors (AVX2). Our accelerated software abides by the specification and reports errors when encountering characters outside of the base64 set. It is available online as free software under a liberal license.
title Faster Base64 Encoding and Decoding Using AVX2 Instructions
topic Mathematical Software
Performance
url https://arxiv.org/abs/1704.00605