High-level Syntax Research Articles

CHR++: An efficient CHR system in C++ with don’t know non-determinism

This article introduces CHR++, an implementation of CHR (Constraint Handling Rules) in C++. CHR++ has been designed to be efficient, user-friendly, and to make it easier to model problems of NP (Non-deterministic Polynomial time) complexity class thanks to the support of don’t know non-determinism. CHR++ conforms to the refined semantics of CHR and provides a high-level syntax similar to the historical CHR implementations in Prolog. It is a powerful system that incorporates many of the high-level optimisations known to date. Like implementations made on top of Prolog, it handles don’t know non-determinism through support for the CHR extension. CHR++ is the first non-Prolog CHR system that natively supports don’t know non-determinism. It makes it easier to model constrained decision or optimisation problems and shows a significant gain in efficiency compared with CHR Prolog systems. It equals or exceeds the fastest CHR systems in Java and C, but is able to tackle a whole class of problems unattainable by those systems.

MEDUSA©: A novel Python-based software ecosystem to accelerate brain-computer interface and cognitive neuroscience research

Background and objective: Neurotechnologies have great potential to transform our society in ways that are yet to be uncovered. The rate of development in this field has increased significantly in recent years, but there are still barriers that need to be overcome before bringing neurotechnologies to the general public. One of these barriers is the difficulty of performing experiments that require complex software, such as brain-computer interfaces (BCI) or cognitive neuroscience experiments. Current platforms have limitations in terms of functionality and flexibility to meet the needs of researchers, who often need to implement new experimentation settings. This work was aimed to propose a novel software ecosystem, called MEDUSA©, to overcome these limitations.Methods: We followed strict development practices to optimize MEDUSA© for research in BCI and cognitive neuroscience, making special emphasis in the modularity, flexibility and scalability of our solution. Moreover, it was implemented in Python, an open-source programming language that reduces the development cost by taking advantage from its high-level syntax and large number of community packages.Results: MEDUSA© provides a complete suite of signal processing functions, including several deep learning architectures or connectivity analysis, and ready-to-use BCI and neuroscience experiments, making it one of the most complete solutions nowadays. We also put special effort in providing tools to facilitate the development of custom experiments, which can be easily shared with the community through an app market available in our website to promote reproducibility.Conclusions: MEDUSA© is a novel software ecosystem for modern BCI and neurotechnology experimentation that provides state-of-the-art tools and encourages the participation of the community to make a difference for the progress of these fields. Visit the official website at https://www.medusabci.com/ to know more about this project.

The High-Level Syntax of the Versatile Video Coding (VVC) Standard

Versatile Video Coding (VVC), a.k.a. ITU-T H.266 | ISO/IEC 23090-3, is the new generation video coding standard that has just been finalized by the Joint Video Experts Team (JVET) of ITU-T VCEG and ISO/IEC MPEG at its <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$19^{\mathrm {th}}$ </tex-math></inline-formula> meeting ending on July 1, 2020. This paper gives an overview of the VVC high-level syntax (HLS), which forms its system and transport interface. Comparisons to the HLS designs in High Efficiency Video Coding (HEVC) and Advanced Video Coding (AVC), the previous major video coding standards, are included. When discussing new HLS features introduced into VVC or differences relative to HEVC and AVC, the reasoning behind the design differences and the benefits they bring are described. The HLS of VVC enables newer and more versatile use cases such as video region extraction, composition and merging of content from multiple coded video bitstreams, and viewport-adaptive 360° immersive media.

MRIReco.jl: An MRI reconstruction framework written in Julia.

The aim of this work is to develop a high-performance, flexible, and easy-to-use MRI reconstruction framework using the scientific programming language Julia. Julia is a modern, general purpose programming language with strong features in the area of signal/image processing and numerical computing. It has a high-level syntax but still generates efficient machine code that is usually as fast as comparable C/C++ applications. In addition to the language features itself, Julia has a sophisticated package management system that makes proper modularization of functionality across different packages feasible. Our developed MRI reconstruction framework MRIReco.jl can therefore reuse existing functionality from other Julia packages and concentrate on the MRI-related parts. This includes common imaging operators and support for MRI raw data formats. MRIReco.jl is a simple to use framework with a high degree of accessibility. While providing a simple-to-use interface, many of its components can easily be extended and customized. The performance of MRIReco.jl is compared to the Berkeley Advanced Reconstruction Toolbox (BART) and we show that the Julia framework achieves comparable reconstruction speed as the popular C/C++ library. Modern programming languages can bridge the gap between high performance and accessible implementations. MRIReco.jl leverages this fact and contributes a promising environment for future algorithmic development in MRI reconstruction.

A distributed API for coordinating AbC programs

Collective adaptive systems exhibit a particular notion of interaction where environmental conditions largely influence interactions. Previously, we proposed a calculus, named AbC, to model and reason about CAS. The calculus proved to be effective by naturally modelling essential CAS features. However, the question on the tradeoff between its expressiveness and its efficiency, when implemented to program CAS applications, is to be answered. In this article, we propose an efficient and distributed coordination infrastructure for AbC. We prove its correctness, and we evaluate its performance. The main novelty of our approach is that AbC components are infrastructure agnostic. Thus the code of a component does not specify how messages are routed in the infrastructure but rather what properties a target component must satisfy. We also developed a Go API, named mathcal {G}{} textit{o}mathcal {A}{} textit{t}, and an Eclipse plugin to program in a high-level syntax which can be automatically used to generate matching Go code. We showcase our development through a non-trivial case study.

Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Owlready has been successfully used in a medical research project. It has been published as Open-Source software and then used by many other researchers. Future developments will focus on the support of vagueness and additional non-monotonic reasoning feature, and automatic dialog box generation.

Overview of SHVC: Scalable Extensions of the High Efficiency Video Coding Standard

This paper provides an overview of Scalable High efficiency Video Coding (SHVC), the scalable extensions of the High Efficiency Video Coding (HEVC) standard, published in the second version of HEVC. In addition to the temporal scalability already provided by the first version of HEVC, SHVC further provides spatial, signal-to-noise ratio, bit depth, and color gamut scalability functionalities, as well as combinations of any of these. The SHVC architecture design enables SHVC implementations to be built using multiple repurposed single-layer HEVC codec cores, with the addition of interlayer reference picture processing modules. The general multilayer high-level syntax design common to all multilayer HEVC extensions, including SHVC, MV-HEVC, and 3D HEVC, is described. The interlayer reference picture processing modules, including texture and motion resampling and color mapping, are also described. Performance comparisons are provided for SHVC versus simulcast HEVC and versus the scalable video coding extension to H.264/advanced video coding.

Rust-Bio: a fast and safe bioinformatics library.

We present Rust-Bio, the first general purpose bioinformatics library for the innovative Rust programming language. Rust-Bio leverages the unique combination of speed, memory safety and high-level syntax offered by Rust to provide a fast and safe set of bioinformatics algorithms and data structures with a focus on sequence analysis. Rust-Bio is available open source under the MIT license at https://rust-bio.github.io. koester@jimmy.harvard.edu Supplementary data are available at Bioinformatics online.

Motion Hooks for the Multiview Extension of HEVC

MV-HEVC refers to the multiview extension of High Efficiency Video Coding (HEVC). At the time of writing, MV-HEVC was being developed by the Joint Collaborative Team on 3D Video Coding Extension Development (JCT-3V) of International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) Moving Picture Experts Group and ITU-T VCEG. Before HEVC itself was technically finalized in January 2013, the development of MV-HEVC had already started and it was decided that MV-HEVC would only contain high-level syntax changes compared with HEVC, i.e., no changes to block-level processes, to enable the reuse of the first-generation HEVC decoder hardware as is for constructing an MV-HEVC decoder with only firmware changes corresponding to the high-level syntax part of the codec. Consequently, any block-level process that is not necessary for HEVC itself but on the other hand is useful for MV-HEVC can only be enabled through so-called hooks. Motion hooks refer to techniques that do not have a significant impact on the HEVC single-view version 1 codec and can mainly improve MV-HEVC. This paper presents techniques for efficient MV-HEVC coding by introducing hooks into the HEVC design to accommodate inter-view prediction in MV-HEVC. These hooks relate to motion prediction, hence named motion hooks. Some of the motion hooks developed by the authors have been adopted into HEVC during its finalization. Simulation results show that the proposed motion hooks provide on average 4% of bitrate reduction for the views coded with inter-view prediction.

The Scalable Extensions of HEVC for Ultra-High-Definition Video Delivery

This article presents an overview of SHVC, the scalable extension of H.265/HEVC. SHVC adopts a scalable coding architecture with only high-level syntax changes relative to its base codec, which allows SHVC to be deployed with significantly reduced implementation cost. SHVC supports a rich set of scalability features. It also addresses the increasing market demand for higher quality and higher value video content delivery by providing a set of desired scalability features with high coding efficiency.

Idris, a general-purpose dependently typed programming language: Design and implementation

AbstractMany components of a dependently typed programming language are by now well understood, for example, the underlying type theory, type checking, unification and evaluation. How to combine these components into a realistic and usable high-level language is, however, folklore, discovered anew by successive language implementors. In this paper, I describe the implementation ofIdris, a new dependently typed functional programming language.Idrisis intended to be ageneral-purposeprogramming language and as such provides high-level concepts such as implicit syntax, type classes anddonotation. I describe the high-level language and the underlying type theory, and present a tactic-based method forelaboratingconcrete high-level syntax with implicit arguments and type classes into a fully explicit type theory. Furthermore, I show how this method facilitates the implementation of new high-level language constructs.

Multi-view Rate Control based on HEVC for 3D Video Services

In this paper, we propose two rate control algorithms for multi-view extension of HEVC with two rate control algorithms adopted in HEVC and analyze the multi-view rate control performance. The proposed multi-view rate controls are designed on HEVC-based multi-view video coding (MV-HEVC) platform with consideration of high-level syntax, inter-view prediction, etc. not only for the base view but also for the extended views using the rate control algorithms based on URQ (Unified Rate-Quantization) and R-lambda model adopted in HEVC. The proposed multi-view rate controls also contain view-wise target bit allocation for providing the compatibility to the base view. By allocating the target bitrates for each view, the proposed multi-view rate control based on URQ model achieved about 1.83% of average bitrate accuracy and 1.73dB of average PSNR degradation. In addition, about 2.97% of average bitrate accuracy and 0.31dB of average PSNR degradation are achieved with the proposed multi-view rate control based on R-lambda model.

Efficient test bitstream generation with an N-way covering algorithm for configurations of high-level syntax elements in video decoders

Test bitstreams are more efficient in testing the video decoders if its bitstream length is shorter while its test coverage is higher. In this paper, a new method to generate efficient bitstreams for functional tests of video decoders is proposed, which also can find and fill up coverage holes. The proposed method employs an n-way covering combinatorial algorithm in finding an efficient configuration set of high-level syntax elements (SEs) and uses a constrained-random algorithm in generating test cases for low-level SEs. With the test bitstreams for MPEG-4 and H.264 decoders generated with the proposed method the experimental results showed that the proposed method is more efficient than the conventional methods. It also showed that the average SE coverage of the generated bitstream set can easily be improved by filling up coverage holes with the proposed method.

Overview of HEVC High-Level Syntax and Reference Picture Management

The increasing proportion of video traffic in telecommunication networks puts an emphasis on efficient video compression technology. High Efficiency Video Coding (HEVC) is the forthcoming video coding standard that provides substantial bit rate reductions compared to its predecessors. In the HEVC standardization process, technologies such as picture partitioning, reference picture management, and parameter sets are categorized as “high-level syntax.” The design of the high-level syntax impacts the interface to systems and error resilience, and provides new functionalities. This paper presents an overview of the HEVC high-level syntax, including network abstraction layer unit headers, parameter sets, picture partitioning schemes, reference picture management, and supplemental enhancement information messages.

System Layer Integration of High Efficiency Video Coding

This paper describes the integration of High Efficiency Video Coding (HEVC) into end-to-end multimedia systems, formats, and protocols such as Real-time transport Protocol, the transport stream of the MPEG-2 standard suite, and dynamic adaptive streaming over the Hypertext Transport Protocol. This paper gives a brief overview of the high-level syntax of HEVC and the relation to the Advanced Video Coding standard (H.264/AVC). A section on HEVC error resilience concludes the HEVC overview. Furthermore, this paper describes applications of video transport and delivery such as broadcast, television over the Internet Protocol, Internet streaming, video conversation, and storage as provided by the different system layers.

Performance Analysis Framework for High-Level Language Applications in Reconfigurable Computing

High-Level Languages (HLLs) for Field-Programmable Gate Arrays (FPGAs) facilitate the use of reconfigurable computing resources for application developers by using familiar, higher-level syntax, semantics, and abstractions, typically enabling faster development times than with traditional Hardware Description Languages (HDLs). However, programming at a higher level of abstraction is typically accompanied by some loss of performance as well as reduced transparency of application behavior, making it difficult to understand and improve application performance. While runtime tools for performance analysis are often featured in development with traditional HLLs for sequential and parallel programming, HLL-based development for FPGAs has an equal or greater need yet lacks these tools. This article presents a novel and portable framework for runtime performance analysis of HLL applications for FPGAs, including an automated tool for performance analysis of designs created with Impulse C, a commercial HLL for FPGAs. As a case study, this tool is used to successfully locate performance bottlenecks in a molecular dynamics kernel in order to gain speedup.

Platform-independent MB-based AVS video standard implementation

AVS1-P2 is the newest video standard of Audio Video coding Standard (AVS) workgroup of China, which provides close performance to H.264/AVC main profile with lower complexity. In this paper, a platform-independent software package with macroblock-based (MB-based) architecture is proposed to facilitate AVS video standard implementation on embedded system. Compared with the frame-based architecture, which is commonly utilized for PC platform oriented video applications, the MB-based decoder performs all of the decoding processes, except the high-level syntax parsing, in a set of MB-based buffers with adequate size for saving the information of the current MB and the neighboring reference MBs to minimize the on-chip memory and to save the time consumed in on-chip/off-chip data transfer. By modifying the data flow and decoding hierarchy, simulating the data transfer between the on-chip memory and the off-chip memory, and modularizing the buffer definition and management for low-level decoding kernels, the MB-based system architecture provides over 80% reduction in on-chip memory compared to the frame-based architecture when decoding 720p sequences. The storage complexity is also analyzed by referencing the performance evaluation of the MB-based decoder. The MB-based decoder implementation provides an efficient reference to facilitate development of AVS applications on embedded system. The complexity analysis provides rough storage complexity requirements for AVS video standard implementation and optimization.

GBFlavor: a new tool for fast and automatic generation of generic bitstream syntax descriptions

The efficient adaptation of scalable media resources is a major point of interest, due to today's tremendous heterogeneity in terms of end-user terminals, network technologies, and coding formats. In order to create a media resource adaptation engine supporting current and future coding formats, a generic (i.e., format-independent) solution is needed. One way to realize this goal is to rely on automatically created textual descriptions of the high-level syntax of binary media resources. MPEG-21 generic Bitstream Syntax Schema (gBS Schema) is a tool that is part of the MPEG-21 Multimedia Framework. It enables the use of generic Bitstream Syntax Descriptions (gBSDs), i.e., textual descriptions in XML, to steer the adaptation of a binary media resource, using format-independent adaptation logic. The major contribution of this paper is the introduction of gBFlavor. It is a novel solution for the automatic and format-agnostic generation of gBSDs. gBFlavor offers the possibility to automatically create a format-specific parser that is able to produce a gBSD, taking as input a particular media resource compliant to the coding format described by the parser. This paper provides an overview of the gBFlavor language, which allows describing the high-level structure of a coding format. The overall functioning of a gBFlavor-enabled adaptation framework is discussed as well. Performance results for two scalable coding formats, in particular H.264/AVC Scalable Video Coding and JPEG2000, show that our proposed solution outperforms existing techniques in terms of execution speed.

Program Control Language: a programming language for adaptive distributed applications

Many distributed applications must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but sophisticated adaptive distributed programs can be extremely challenging to design, implement and debug. This paper proposes a language called Program Control Language (PCL) that provides a novel means of specifying adaptations in distributed applications. PCL is based on an abstract, global representation of a distributed program (a static task graph), which enables a programmer to reason about and to describe a wide range of application-specific adaptation strategies at a high level, using a few key mechanisms. PCL provides simple high-level syntax for local and remote adaptation operations, local and remote performance monitoring (and aggregation), and for performing adaptations synchronously or asynchronously with respect to the execution of the application process initiating the adaptation. The global task graph representation enables remote performance metrics and adaptation operations to be specified in simple global terms by any process, and the compiler and runtime system automatically perform the communication and synchronization required for the remote operations. The paper describes the conceptual adaptation framework, the PCL language, and our implementation of the PCL compiler and runtime system. The paper uses three adaptative applications examples to illustrate the capabilities and benefits of PCL, and to show experimentally that the performance overheads of using PCL for implementing an adaptive application are negligible.

Local and global characteristics in the development of morphosyntax by French children

Statistical analysis of morphosyntax acquisition in French children aged two to four can be conducted at two levels. At the local level, regularities in the immediate lexical context of a word are evaluated by computing the proportion of pairs of consecutive words (e.g., such as) produced by children which are also produced in the same order by adults. At the global level, regularities in collected samples of children's language production are evaluated by computing the correlation between child distribution and adult distribution of open-class lexical categories in language production samples. Data from child language production show that irregularities evolve at the global level and tend to disappear over time. In contrast, local regularities already present at the age of two remain stable during maturation. To account for these findings, it is suggested that: (a) local regularities are a consequence of the reproduction of the adult's morphosyntax, and global irregularities a consequence of the randomness of a child's cognition and understanding of the world; and (b) high-level syntax - as opposed to morphosyntax - appears only later, as a development of local-level rules, and global regularities are a consequence of high-level syntax.