FIFO Queue Research Articles

Iterative Reconstruction of Micro Computed Tomography Scans Using Multiple Heterogeneous GPUs.

Graphics processing units (GPUs) facilitate massive parallelism and high-capacity storage, and thus are suitable for the iterative reconstruction of ultrahigh-resolution micro computed tomography (CT) scans by on-the-fly system matrix (OTFSM) calculation using ordered subsets expectation maximization (OSEM). We propose a finite state automaton (FSA) method that facilitates iterative reconstruction using a heterogeneous multi-GPU platform through parallelizing the matrix calculations derived from a ray tracing system of ordered subsets. The FSAs perform flow control for parallel threading of the heterogeneous GPUs, which minimizes the latency of launching ordered-subsets tasks, reduces the data transfer between the main system memory and local GPU memory, and solves the memory-bound of a single GPU. In the experiments, we compared the operation efficiency of OS-MLTR for three reconstruction environments. The heterogeneous multiple GPUs with job queues for high throughput calculation speed is up to five times faster than the single GPU environment, and that speed up is nine times faster than the heterogeneous multiple GPUs with the FIFO queues of the device scheduling control. Eventually, we proposed an event-triggered FSA method for iterative reconstruction using multiple heterogeneous GPUs that solves the memory-bound issue of a single GPU at ultrahigh resolutions, and the routines of the proposed method were successfully executed on each GPU simultaneously.

The Saturated Multiserver Job Queuing Model with Two Classes of Jobs: Exact and Approximate Results

We study a Multiserver Job Queuing Model (MJQM), i.e., a FIFO (First-In-First-Out) queue in which jobs request varying numbers of servers. Our investigation focuses on the saturation analysis of MJQM with two job classes. Jobs in the first class need only one server for an exponentially distributed service time, while jobs in the second class require either all servers or a fraction of them. We provide exact results for the scenario in which jobs in the second class require all servers and have generally distributed service times. Additionally, we develop an accurate approximate model of the MJQM behavior when jobs in the second class require a fraction of the available servers, and have exponentially distributed service times.

Enhancing pore network extraction performance via seed-based pore region growing segmentation

Pore-scale modeling, aided by imaging advancements and computational power, is now a vital tool for comprehending fluid flow and transport in porous media. It allows detailed exploration of pore structures and analysis of fluid dynamics and mass transport at smallest scales. This work presents the Pore Region Growing (PREGO) Algorithm, a novel approach to address segmentation challenges encountered in large-sized 3D images used for pore network modeling. The algorithm overcomes limitations of traditional methods like the watershed algorithm, in both computational time and memory of the pore segmentation. Like the watershed method, the proposed work involves identifying seed points, then grows each to fill their respective basis. The algorithm differs from existing approaches in that it efficiently prioritizes and grows the seed points using a FIFO queue, resulting in well-defined segmentation with clear and smooth boundaries between neighboring regions. The output was validated by demonstrating the algorithm's robustness in predicting diffusive behavior and viscous fluid flow within the pore phase network, with excellent agreement in comparison to lattice Boltzmann simulations and experimental data. The proposed algorithm was also shown to accurately predict transport properties under varying porosity, and different types of real porous media images. The evaluation of the Intersection over Union (IoU) and Dice Similarity Coefficient (DSC) metrics revealed that the PREGO technique had a maximum error of 5.44%, whereas the Watershed method exhibited a comparatively higher error rate of 22.3%. Structural analysis of physical properties revealed PREGO captures pore and throat sizes in close agreement with existing approaches. Crucially, computational performance analysis demonstrated its efficiency, significantly reducing memory consumption by 50% and CPU time speed up of 3.35X compared to the standard watershed algorithm using a priority queue.

Research and analysis of FIFO related working principles

An asynchronous FIFO is a classic circuit device used for caching data and accommodating the frequency of asynchronous signals. With the continuous improvement of technology, the advantages of this device in real-time transmission, multi-core processing, and data acquisition have become more apparent. As a result, the original structure has been optimized and extended using algorithm and design techniques to achieve greater efficiency and applicability in various academic and industrial applications. This article discusses several methods for optimizing FIFO in different aspects and examines how an unlocked FIFO queue is applied in a CAN bus data acquisition system, as well as its use in data hybrid framing technology. The findings show that FIFO performs exceptionally well as a cache structure, particularly in situations involving large amounts of data acquisition and real-time procession. The various optimization techniques discussed in this article include using pipeline registers, implementing a dual-clock FIFO, and employing Gray-code-based pointers. These techniques can increase the speed and reduce the power consumption of FIFO, thereby improving its overall efficiency. In addition, the article introduces the unlocked FIFO queue, which provides more flexibility than conventional locked FIFOs. Unlocked FIFO queues allow multiple cores to access the buffer simultaneously, which makes them ideal for high-performance systems. Finally, the article explores the application of FIFO in CAN bus data acquisition systems, where it is utilized as a buffer between the bus and other devices. Additionally, the use of FIFO in data hybrid framing technology is discussed, where it is essential for maintaining the integrity of the data stream.

Making programmable packet scheduling time-sensitive with a FIFO queue

Time-Sensitive Networking (TSN) is an emerging technology for real-time and non-real-time hybrid networked systems. TSN is standardized by IEEE 802.1 TSN Task Group and is becoming widely used in various scenarios including the cloud network. However, existing programmable packet schedulers such as PIFO, PIEO, and AIFO in programmable switches either lack the ability to express most scheduling algorithms in TSN or introduce intolerable on-chip memory overhead (e.g., strict-priority queues). This makes programmable switches and NICs incapable of providing deterministic forwarding. In this paper, we present AIAO (Admission-In-Admission-Out), a new set of programmable scheduling primitives using just a single FIFO to support typical TSN scheduling algorithms, as well as other popular work-conserving algorithms. AIAO is inspired by AIFO but improves it with a group of high-speed packet ingress/egress admission control triggered by high-precise and globally synchronized time, thus being able to support time-sensitive scheduling. We implement AIAO and evaluate it with FPGA-based TSN switches. The preliminary results show that AIAO guarantees correctness for a typical TSN scheduling algorithm with minimal logic and memory overhead.

Precise Subtyping for Asynchronous Multiparty Sessions

Session subtyping is a cornerstone of refinement of communicating processes: A process implementing a session type (i.e., a communication protocol) T can be safely used whenever a process implementing one of its supertypes T ′ is expected, in any context, without introducing deadlocks nor other communication errors. As a consequence, whenever T ≤ T ′ holds, it is safe to replace an implementation of T ′ with an implementation of the subtype T , which may allow for more optimised communication patterns. We present the first formalisation of the precise subtyping relation for asynchronous multiparty sessions. We show that our subtyping relation is sound (i.e., guarantees safe process replacement, as outlined above) and also complete : Any extension of the relation is unsound. To achieve our results, we develop a novel session decomposition technique, from full session types (including internal/external choices) into single input/output session trees (without choices). We cover multiparty sessions with asynchronous interaction, where messages are transmitted via FIFO queues (as in the TCP/IP protocol), and prove that our subtyping is both operationally and denotationally precise. Our session decomposition technique expresses the subtyping relation as a composition of refinement relations between single input/output trees and provides a simple reasoning principle for asynchronous message optimisations.

Design of fork-join networks of First-In-First-Out and infinite-server queues applied to clinical chemistry laboratories

This paper considers optimal design of queueing networks in which each node consists of a single-server FIFO queue and an infinite-server queue, which is referred to as incubation queue. Upon service completion at a FIFO queue, a job splits (forks) into two parts: the first part is routed to the next node on its route, and the second part is placed in the incubation queue. Routing of the jobs of multiple types is governed by a central decision maker that decides on the routes for each job type and aims to minimize the mean turnaround time of the jobs, i.e., the time spent in the system until service completion at the FIFO queue in the last node, and at all incubation queues on the job’s route, which may be viewed as a join operation. We provide explicit results for the turnaround time when all service and inter-arrival time distributions are exponential and invoke the Queueing Network Analyzer when these distributions are general. We then develop a Simulated Annealing approach to find the optimal routing configuration. We apply our approach to determine the optimal routing configuration in a chemistry analyzer line.

Packet rank-aware active queue management for programmable flow scheduling

Flow scheduling is crucial in improving network Quality of Service (QoS). According to different optimization goals, many scheduling algorithms (e.g., STFQ, pFabric, SRPT, WFQ) have emerged in network. However, these scheduling algorithms are bound with hardware, which are only applicable to fixed network scenarios. Push-In First-Out (PIFO) queues are proposed as a queue abstraction to support programmable packet scheduling, but implementing them in hardware is difficult. We present a general framework named PR-AQM, which uses limited number of FIFO queues to approximate PIFO behavior. The core idea of PR-AQM is to perform Active Queue Management (AQM) on programmable data plane by capturing packet rank distribution and queue congestion level in real time. Specifically, PR-AQM can dynamically adjust the mapping between packet ranks and queues according to the delay status of different priority queues, thus efficiently achieving priority scheduling of packets. We carry out extensive simulations and implement PR-AQM prototype in Tofino switches to evaluate the performance of PR-AQM. Experimental results show that compared with state-of-the-art algorithms, PR-AQM can adapt well to different scheduling algorithms, and achieve better performance by reducing the average flow completion time for short flows up to 45%.

Data Dissemination in VANETs Using Particle Swarm Optimization.

A vehicular Ad-Hoc Network (VANET) is a type of Mobile Ad-Hoc Networks (MANETs) that uses wireless routers inside each vehicle to act as a node. The need for effective solutions to urban traffic congestion issues has increased recently due to the growing number of automobile connections in the car communications system. To ensure a high level of service and avoid unsafe situations brought on by congestion or a broadcast storm, data dissemination in a VANET network requires an effective approach. Effective multi-objective optimization methods are required to tackle this because of the implied competing nature of multi-metric approaches. A meta-heuristic technique with a high level of solution interactions can handle efficient optimization. To accomplish this, a meta-heuristic search algorithm particle optimization was chosen. In this paper, we have created a network consisting of vehicles as nodes. The aim is to send emergency messages immediately to the stationary nodes. The normal messages will be sent to the FIFO queue. To send these messages to a destination node, multiple routes were found using Time delay-based Multipath Routing (TMR) method, and to find the optimal and secure path Particle Swarm Optimization (PSO) is used. Our method is compared with different optimization methods such as Ant Colony Optimization (ACO), Firefly Optimization (FFO), and Enhanced Flying Ant Colony Optimization (EFACO). Significant improvements in terms of throughput and packet loss ratio, reduced end-to-end delay, rounding overhead ratio, and the energy consumption are revealed by the experimental results.

A Partial Order View of Message-Passing Communication Models

There is a wide variety of message-passing communication models, ranging from synchronous "rendez-vous" communications to fully asynchronous/out-of-order communications. For large-scale distributed systems, the communication model is determined by the transport layer of the network, and a few classes of orders of message delivery (FIFO, causally ordered) have been identified in the early days of distributed computing. For local-scale message-passing applications, e.g., running on a single machine, the communication model may be determined by the actual implementation of message buffers and by how FIFO queues are used. While large-scale communication models, such as causal ordering, are defined by logical axioms, local-scale models are often defined by an operational semantics. In this work, we connect these two approaches, and we present a unified hierarchy of communication models encompassing both large-scale and local-scale models, based on their concurrent behaviors. We also show that all the communication models we consider can be axiomatized in the monadic second order logic, and may therefore benefit from several bounded verification techniques based on bounded special treewidth.

Multiparty half-duplex systems and synchronous communications

FIFO automata are finite state machines communicating through FIFO queues. They can be used, for instance, to model distributed protocols. Due to the unboundedness of the FIFO queues, several verification problems are undecidable for these systems. In order to model check such systems, one may look for decidable subclasses of FIFO systems. Binary half-duplex systems are systems of two FIFO automata exchanging over a half-duplex channel. They were studied by Cécé and Finkel who established the decidability in polynomial time of several properties. There is no obvious way to generalize the half-duplex property to multiparty systems. Cécé and Finkel proposed some generalizations but concluded that their notions of multiparty half-duplex systems were either too restrictive or too expressive.We explore in this paper other ways of generalizing half-duplex systems to multiparty. First, we introduce systems realizable with synchronous communications (RSC) and we show that RSC systems generalize half-duplex systems and retain the same good properties as binary half-duplex systems. Second, we introduce a notion of multiparty half-duplex systems that differs from the ones explored by Cécé and Finkel, and we show two results about this notion: (1) for mailbox communications, half-duplex systems are essentially the same as RSC systems, and (2) for peer-to-peer communications, the two notions are distinct, and RSC systems appear to be “the good one”, since peer-to-peer half-duplex systems are Turing powerful.

Coloured Petri Nets for Temporal Performance Evaluation of Distributed Control Systems—Application to a FIFO Queue

Temporal performances (like response time) of distributed control systems must be measurable for critical systems. The delay and reliability requirements require us to develop an exhaustive method to evaluate these performances through the most accurate models, such as (max,+) algebra combined with timed event graphs. Among the common mechanisms encountered in a distributed control system, the FIFO policy remains one of the most used and cannot be modeled with timed event graphs. We show that the formalism of timed coloured Petri nets described in the (max,+) algebra can model the FIFO queue of a Programmable Logic Controller communication module. We also aim to reveal some exciting features of coloured Petri nets when analytically evaluating temporal performances. We present, therefore, a Timed Coloured Petri net modeling the emptying of a FIFO queue with a periodic task, and the formulas of delays associated with the induced system of (max, +) equations. We also test the consistency of our bounds in a numerical application of our model with positive results.

Time-Optimal Coordination for Connected and Automated Vehicles at Adjacent Intersections

In this paper, we provide a hierarchical coordination framework for connected and automated vehicles (CAVs) at two adjacent intersections. This framework consists of an upper-level scheduling problem and a low-level optimal control problem. By partitioning the area around two adjacent intersections into different zones, we formulate a scheduling problem for each individual CAV aimed at minimizing its total travel time. For each CAV, the solution of the upper-level problem designates the arrival times at each zones on its path which becomes the inputs of the low-level problem. The solution of the low-level problem yields the optimal control input (acceleration/deceleration) of each CAV to exit the intersections at the time specified in the upper-level scheduling problem. We validate the performance of our proposed hierarchical framework through extensive numerical simulations and comparison with signalized intersections, centralized scheduling, and FIFO queuing policy.

Cameleer A deductive verification tool for OCaml

OCaml is particularly well-fitted for formal verification. On one hand, it is a multi-paradigm language with a well-defined semantics, allowing one to write clean, concise, type-safe, and efficient code. On the other hand, it is a language of choice for the implementation of sensible software, e.g., industrial compilers, proof assistants, and automated solvers. Yet, with the notable exception of some interactive tools, formal verification has been seldom applied to OCaml-written programs. In this paper, we present the ongoing project Cameleer, aiming for the development of a deductive verification tool for OCaml, with a clear focus on proof automation. We leverage on the recently proposed GOSPEL, Generic OCaml SPE cification Language, to attach rigorous, yet readable, behavioral specification to OCaml code. The formally-specified program is fed to our toolchain, which translates it into an equivalent program in WhyML, the programming and specification language of the Why3 verification framework. Finally, Why3 is used to compute verification conditions for the generated program, which can be discharged by off-the-shelf SMT solvers. We present successful applications of the Cameleer tool to prove functional correctness of several significant case studies, like FIFO queues (ephemeral and applicative implementations) and leftist heaps, issued from existing OCaml libraries.

Approximate and Deployable Shortest Remaining Processing Time Scheduler

The scheduling policy installed on switches of datacenters plays a significant role on congestion control. Shortest-Remaining-Processing-Time (SRPT) achieves the near-optimal average message completion time (MCT) in various scenarios, but is difficult to deploy as viewed by the industry. The reasons are two-fold: 1) many commodity switches only provide FIFO queues, and 2) the information of remaining message size is not available. Recently, the idea of emulating SRPT using only a few FIFO queues and the original message size has been coined as the approximate and deployable SRPT (ADS) design. In this paper, we provide the first theoretical study on the optimal ADS design. Specifically, we first characterize a wide range of feasible ADS scheduling policies via a unified framework, and then derive the steady-state MCT, slowdown, and impoliteness in the M/G/1 setting. Hence we formulate the optimal ADS design as a non-linear combinatorial optimization problem, which aims to minimize the average MCT given the available FIFO queues. We also take into account the proportional fairness and temporal fairness constraints based on the maximal slowdown and impoliteness, respectively. The optimal ADS design problem is NP-hard in general, and does not exhibit monotonicity or sub-modularity. We leverage its decomposable structure and devise an efficient algorithm to solve the optimal ADS policy. We carry out extensive flow-level simulations and packet-level experiments to evaluate the proposed optimal ADS design. Results show that the optimal ADS policy installed on eight FIFO queues is capable of emulating the true SRPT.

ANALISIS ANTREAN BUS NONPATAS JALUR TIMUR TERMINAL TIRTONADI KOTA SURAKARTA MENGGUNAKAN METODE BAYESIAN

The queuing system relates to customers and service facilities. Queuing theory designs service facilities to address service requests. Queues occur if the service capacity is not sufficient to provide services to many customers. The queuing phenomenon occurs on non-patas buses on the eastern route of Tirtonadi Terminal, Surakarta with Surabaya, Karanganyar, Wonogiri, Purwodadi and Pedesaan buses. The Bayesian method combines information from current research and previous studies with similar cases, and produces a posterior distribution to form a queuing system model and measure of service system performance. The bus queuing system model for Surabaya, Karanganyar, Wonogiri and Purwodadi has a Gamma-distributed arrival and service pattern. Pedesaan buses has an arrival pattern with a Gamma distribution and a service pattern with an Inverse Gamma distribution. Each line has 1 bus line as a service system, FIFO queue discipline, the number of customer capacity and call sources is not limited. The Surabaya buses has the highest probability of 93.49% that the line is idle and the Pedesaan buses has the highest probability that the line will be busy serving at 89.50%. The queuing system are considered good because the five lines of service facilities are able to meet customer needs. Keywords: Tirtonadi Terminal, Bayesian, Posterior Distribution, Queue Models, System Performance Measures

BQ: A Lock-Free Queue with Batching

Concurrent data structures provide fundamental building blocks for concurrent programming. Standard concurrent data structures may be extended by allowing a sequence of operations to be submitted as a batch for later execution. A sequence of such operations can then be executed more efficiently than the standard execution of one operation at a time. In this article, we develop a novel algorithmic extension to the prevalent FIFO queue data structure that exploits such batching scenarios. An implementation in C++ on a multicore demonstrates significant performance improvement of more than an order of magnitude (depending on the batch lengths and the number of threads) compared to previous queue implementations.

AQM based on the queue length: A real-network study.

Active Queue Management (AQM) is recommended by Internet Engineering Task Force to mitigate the bufferbloat phenomenon in the Internet. In this paper, we show the results of comprehensive measurements carried out in our university network, in which a device with an AQM algorithm, designed and programmed for this purpose, was running. The implemented AQM algorithm was based on the dropping function, i.e. arriving packets were dropped randomly, with the probability being a function of the queue length. Several different dropping function forms, proposed in the networking literature, were used, in addition to the classic FIFO queue (no AQM). The experiment lasted over a month, during which the state of the network was measured and recorded several thousand times. This made the results independent of the natural fluctuations of the users’ behavior and the network load. Conclusions on the general performance improvement offered by the implemented AQM, as well as the differences in the performance between particular forms of the dropping function, were reached. Some of these conclusions differ from those drawn previously from simulations. This underlines the need for carrying measurements of new AQMs in real, operating networks, with complex, natural traffic.

The Forward Slice Core: A High-Performance, Yet Low-Complexity Microarchitecture

Superscalar out-of-order cores deliver high performance at the cost of increased complexity and power budget. In-order cores, in contrast, are less complex and have a smaller power budget, but offer low performance. A processor architecture should ideally provide high performance in a power- and cost-efficient manner. Recently proposed slice-out-of-order (sOoO) cores identify backward slices of memory operations which they execute out-of-order with respect to the rest of the dynamic instruction stream for increased instruction-level and memory-hierarchy parallelism. Unfortunately, constructing backward slices is imprecise and hardware-inefficient, leaving performance on the table. In this article, we propose Forward Slice Core (FSC ), a novel core microarchitecture that builds on a stall-on-use in-order core and extracts more instruction-level and memory-hierarchy parallelism than slice-out-of-order cores. FSC does so by identifying and steering forward slices (rather than backward slices) to dedicated in-order FIFO queues. Moreover, FSC puts load-consumers that depend on L1 D-cache misses on the side to enable younger independent load-consumers to execute faster. Finally, FSC eliminates the need for dynamic memory disambiguation by replicating store-address instructions across queues. Considering 3-wide pipeline configurations, we find that FSC improves performance by 27.1%, 21.1%, and 14.6% on average compared to Freeway, the state-of-the-art sOoO core, across SPEC CPU2017, GAP, and DaCapo, respectively, while at the same time incurring reduced hardware complexity. Compared to an OoO core, FSC reduces power consumption by 61.3% and chip area by 47%, providing a microarchitecture with high performance at low complexity.

AXI-IC^{RT}: Towards a Real-Time AXI-Interconnect for Highly Integrated SoCs

In modern real-time heterogeneous System-on-Chips (SoCs), ensuring the predictability of interconnects is becoming increasingly important. Most of the existing interconnects are mainly designed to achieve high throughput, with their micro-architectures usually based on FIFO queues. The FIFO-based design prevents transaction prioritization based on importance and leads to occurrences of physical priority inversion. Such problems lead to difficulties in ensuring transaction predictability, especially when the system scales to a large number of elements. In this paper, we introduce AXI-Interconnect^{rt} (AXI-IC^{rt}, for short) -- a real-time AXI interconnect for heterogeneous SoCs, which redefines the micro-architecture of interconnects by enabling random accesses of buffered transactions and organizing transactions through compositional scheduling. This hardware-software co-design approach provides predictable and scalable real-time performance for highly integrated SoCs.