4 research outputs found
Animated GIF optimization by adaptive color local table management
After thirty years of the GIF file format, today is becoming more popular
than ever: being a great way of communication for friends and communities on
Instant Messengers and Social Networks. While being so popular, the original
compression method to encode GIF images have not changed a bit. On the other
hand popularity means that storage saving becomes an issue for hosting
platforms. In this paper a parametric optimization technique for animated GIFs
will be presented. The proposed technique is based on Local Color Table
selection and color remapping in order to create optimized animated GIFs while
preserving the original format. The technique achieves good results in terms of
byte reduction with limited or no loss of perceived color quality. Tests
carried out on 1000 GIF files demonstrate the effectiveness of the proposed
optimization strategy
Using MapReduce Streaming for Distributed Life Simulation on the Cloud
Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum