Static 3D Triangle Mesh Compression Overview

3D triangle meshes are extremely used to model discrete surfaces, and almost always represented with two tables: one for geometry and another for connectivity. While the raw size of a triangle mesh is of around 200 bits per vertex, by coding cleverly (and separately) those two distinct kinds of information it is possible to achieve compression ratios of 15:1 or more. Different techniques must be used depending on whether single-rate vs. progressive bitstreams are sought; and, in the latter case, on whether or not hierarchically nested meshes are desirable during reconstructio

Pakkausmenetelmät hajautetussa aikasarjatietokannassa

Rise of microservices and distributed applications in containerized deployments are putting increasing amount of burden to the monitoring systems. They push the storage requirements to provide suitable performance for large queries. In this paper we present the changes we made to our distributed time series database, Hawkular-Metrics, and how it stores data more effectively in the Cassandra. We show that using our methods provides significant space savings ranging from 50 to 90% reduction in storage usage, while reducing the query speeds by over 90\% compared to the nominal approach when using Cassandra. We also provide our unique algorithm modified from Gorilla compression algorithm that we use in our solution, which provides almost three times the throughput in compression with equal compression ratio.Hajautettujen järjestelmien yleistyminen on aiheuttanut valvontajärjestelmissä tiedon määrän kasvua, sillä aikasarjojen määrä on kasvanut ja niihin talletetaan useammin tietoa. Tämä on aiheuttanut kasvavaa kuormitusta levyjärjestelmille, joilla on ongelmia palvella kasvavia kyselyitä Tässä paperissa esittelemme muutoksia hajautettuun aikasarjatietokantaamme, Hawkular-Metricsiin, käyttäen hyödyksi tehokkaampaa tiedon pakkausta ja järjestelyä kun tietoa talletetaan Cassandraan. Nopeutimme kyselyjä lähes kymmenkertaisesti ja samalla pienensimme levytilavaatimuksia aineistosta riippuen 50-95%. Esittelemme myös muutoksemme Gorilla pakkausalgoritmiin, jota hyödynnämme tulosten saavuttamiseksi. Muutoksemme nopeuttavat pakkaamista melkein kolminkertaiseksi alkuperäiseen algoritmiin nähden ilman pakkaustehon laskua

Decoding billions of integers per second through vectorization

In many important applications -- such as search engines and relational database systems -- data is stored in the form of arrays of integers. Encoding and, most importantly, decoding of these arrays consumes considerable CPU time. Therefore, substantial effort has been made to reduce costs associated with compression and decompression. In particular, researchers have exploited the superscalar nature of modern processors and SIMD instructions. Nevertheless, we introduce a novel vectorized scheme called SIMD-BP128 that improves over previously proposed vectorized approaches. It is nearly twice as fast as the previously fastest schemes on desktop processors (varint-G8IU and PFOR). At the same time, SIMD-BP128 saves up to 2 bits per integer. For even better compression, we propose another new vectorized scheme (SIMD-FastPFOR) that has a compression ratio within 10% of a state-of-the-art scheme (Simple-8b) while being two times faster during decoding.Comment: For software, see https://github.com/lemire/FastPFor, For data, see http://boytsov.info/datasets/clueweb09gap

File compression using typogenetic computation

Typogenetic algorithms are a break from classical approaches to computation. Based on gene expression and intercellular processes, typo-genetic computation can offer a new approach to the algorithmic problems of system security, data compression and encryption. The method has a potential of much higher compression ratios at the limited computational costs i.e. processing time. This paper presents a formal system based on typogenetics for the purposes of compression. Lossless data compression is an important part of computer science. While the ability to reduce consumption of hard disk space or transmission bandwidth through statistical redundancy has served well in the past, the explosive growth in high quality media content (*.mp3, *.mpg) on the internet in the past few years have highlighted the limitations of traditional statistical techniques for compression. © 2008 IEEE