1,625 research outputs found
The Sound Manifesto
Computing practice today depends on visual output to drive almost all user
interaction. Other senses, such as audition, may be totally neglected, or used
tangentially, or used in highly restricted specialized ways. We have excellent
audio rendering through D-A conversion, but we lack rich general facilities for
modeling and manipulating sound comparable in quality and flexibility to
graphics. We need co-ordinated research in several disciplines to improve the
use of sound as an interactive information channel.
Incremental and separate improvements in synthesis, analysis, speech
processing, audiology, acoustics, music, etc. will not alone produce the
radical progress that we seek in sonic practice. We also need to create a new
central topic of study in digital audio research. The new topic will assimilate
the contributions of different disciplines on a common foundation. The key
central concept that we lack is sound as a general-purpose information channel.
We must investigate the structure of this information channel, which is driven
by the co-operative development of auditory perception and physical sound
production. Particular audible encodings, such as speech and music, illuminate
sonic information by example, but they are no more sufficient for a
characterization than typography is sufficient for a characterization of visual
information.Comment: To appear in the conference on Critical Technologies for the Future
of Computing, part of SPIE's International Symposium on Optical Science and
Technology, 30 July to 4 August 2000, San Diego, C
Faster Base64 Encoding and Decoding Using AVX2 Instructions
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.Comment: software at https://github.com/lemire/fastbase6
Faster Base64 Encoding and Decoding Using AVX2 Instructions
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.Comment: software at https://github.com/lemire/fastbase6
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