Genomic sequencing data contain three different data fields: read names, quality values, and nucleotide sequences. In this work, a variety of entropy encoders and com-pression algorithms were benchmarked in terms of compression-decompression rates and times separately for each data field as raw data from FASTQ files (implemented in the Fastq analysis script) and in MPEG-G uncompressed descriptor symbols de-coded from MPEG-G bitstreams (implemented in the symbols analysis script). The result of this benchmark is then compared to the performance of CABAC, which is the encoder used in first edition of the ISO /IEC MPEG-G standard for all types of descriptors, since CABAC was the best performing in terms of compression rates for the three types of data, thus providing overall better compression rates compared to other entropy coders in total. However, in some use cases encoding and decoding speed might be of higher interest than compression, and for specific datasets, types of data, or descriptor streams, other entropy coders might provide higher speed and/or better compression performance than CABAC.

High-throughput sequencing of RNA molecules has enabled the quantitative analysis of gene expression at the expense of storage space and processing power. To alleviate these problems, lossy compression methods of the quality scores associated to RNA sequencing data have recently been proposed, and the evaluation of their impact on downstream analyses is gaining attention. In this context, this work presents a first assessment of the impact of lossily compressed quality scores in RNA sequencing data on the performance of some of the most recent tools used for differential gene expression.

High-throughput sequencing of RNA molecules has enabled the quantitative analysis of the expression of genes at the expense of storage space and processing power. To help alleviate these problems, lossy compression methods of the quality scores associated to RNA sequence data have recently been proposed, and the evaluation of their impact on downstream analysis is gaining attention. This work presents a first assessment of the impact of lossly compressed quality scores in RNA sequence data on the performance of some of the most recent tools used for differential gene expression.

This paper provides the specification and an initial validation of an evaluation framework for the comparison of lossy compressors of genome sequencing quality values. The goal is to define reference data, test sets, tools and metrics that shall be used to evaluate the impact of lossy compression of quality values on human genome variant calling. The functionality of the framework is validated referring to two state-of-the-art genomic compressors. This work has been spurred by the current activity within the ISO/IEC SC29/WG11 technical committee (a.k.a. MPEG), which is investigating the possibility of starting a standardization activity for genomic information representation.

Minimizing buffer sizes of dynamic dataflow implementations without introducing deadlocks or reducing the design performance is in general an important and useful design objective. Indeed, buffer sizes that are too small causing a system to deadlock during execution, or dimensioning unnecessarily large sizes leading to a resource inefficient design are both not a desired design option. This paper presents an implementation, validation, and comparison of several buffer size optimization techniques for the generic class of dynamic dataflow model of computation called the dataflow process network. The paper presents an heuristic capable of finding a close-to-minimum buffer size configuration for deadlock-free executions, and a methodology to efficiently explore different configurations for feasible design alternatives. The approach is demonstrated using as experimental design case, an MPEG-4 AVC/H.264 decoder implemented on an FPGA.

MPEG High Efficient Video Coding (HEVC) is likely to emerge as the video coding standard for HD and Ultra-HD TV resolutions. The two elements that push HEVC beyond the previous standards are a higher compression efficiency of about a factor of two, and the introduction of new coding tools, tiles and wavefront that are intended to ease the largely increased encoding complexity particularly for Ultra HD resolutions such as 4K and 8K. However, for HEVC decoder implementations, the achievement of the desired performance on massive parallel platforms cannot rely on the use of such optional (not enforced by MPEG profiles) tools. This paper reports results about the intrinsic parallelism of compliant HEVC decoding algorithms obtained by analyzing a dataflow implementation written using the standard language specified in ISO/IEC 23001-4 and structured attempting to maximize the algorithmic potential parallelism. The experimental results show what is the parallelism achieved by different dataflow architectures and how it can be further combined with the parallelism achieved by relying on tiles and wavefront, whenever they would be available, for porting a compliant HEVC decoder on massive parallel many-core platforms.

The MPEG-4 audio standard provides several toolsets for natural and synthetic sound coding. Among them, the most innovative in terms of multimedia applications is Structured Audio (SA), which implements a high level, structured description of sound instead of the usual compression techniques based on psychoacoustics and subband analysis. SA permits to encode synthesis and processing algorithms by its Structured Audio Orchestra Language (SAOL), and it can theoretically be used to specify any other audio decoder. This great flexibility introduces a challenging implementation problem, which in a normative framework has to be solved by a systematic approach. In the first part of the paper, it is described how the SA decoding process can be analyzed in a platform independent way in order to determine the fundamental figures of this coding technique; it is then shown how the proposed method is being used for the MPEG-4 SA conformance test. In the second part the design of a virtual digital signal processor (DSP) architecture is presented, based on the results of the complexity analysis. This architecture is able to exploit the intrinsic data level parallelism of many Audio algorithms and to consistently reduce the implementation cost. Experimental results prove the effectiveness of the approach and its suitability for implementations on modern superscalar DSPs and multimedia processors.

The new MPEG-4 audio standard provides two toolsets for synthetic audio generation, audio processing and multimedia content description called Structured Audio (SA) and Binary Format for Scenes (BIFS). Moving from a systematic analysis of SA and from the implementation of an efficient SA decoder, this paper describes the design of a virtual DSP architecture able to exploit the data level parallelism contained in many typical audio processing algorithms. The proposed virtual DSP architecture shows good performance on general purpose platforms and can be easily adapted and optimized for parallel superscalar devices. The porting and results on a V-LIW DSP device confirm the effectiveness and flexibility of the approach, which is particularly suitable for standalone embedded solutions.

The MPEG-4 audio standard provides a toolset for audio synthesis and audio processing, i.e. structured audio (SA). SA permits one to describe algorithms through its Structured Audio Orchestra Language (SAOL) programming language. Unlike some other languages of the same type, SAOL has a sample-by-sample execution structure, and this makes particularly important the overhead computation in case of an interpreted decoder implementation. This paper describes the design of an efficient virtual architecture able to exploit the data level parallelism contained in many audio synthesis and processing algorithms and to consistently reduce the implementation overhead through a block-by-block execution.