Thread Scheduling Algorithms Research Articles

A scheduling algorithm based on critical factors for heterogeneous multicore processors

SummaryAs the development of chip manufacturing technology slows down, high‐performance processors often have high energy consumption and high heat generation. Therefore, heterogeneous multi‐core processors become more and more popular, and the heterogeneous multi‐core processors is adopted to execute programs. At present, the general program consists of multiple threads. To reach goals of accelerating program execution and reducing energy consumption and heat generation of system, a suitable thread scheduling algorithm for heterogeneous multi‐core processors is needed. In this article, a thread scheduling algorithm based on multiple critical scheduling factors is proposed. First, a prediction model of thread performance and energy consumption is used to predict the core sensitivity of threads. Then, critical threads are judged and accelerated by collecting the synchronization information between threads. Finally, the load balancing method based on the computing power of cores and the core sensitivity of threads is employed to perform system load balancing, which ensures the fairness of the scheduling. Several experiments are provided, and the results show that the proposed algorithm can obtain better performance of thread schedule.

Compilation Optimization of DCU-oriented OpenMP Thread Scheduling

OpenMP is one of the mainstream parallel programming models in recent years. After version 4.0, OpenMP introduced a new target instruction to increase the functionality of heterogeneous programming, called OpenMP Offload. For the domestic heterogeneous platform DCU, the thread scheduling algorithm under OpenMP parallel computing has low performance in the default mode, which does not take the best advantage of GPU parallel computing and has wasted resources. To address this problem, this paper performs algorithm improvement at the compiler level, analyzes the available resources of the system by combining the DCU hardware facilities, then further parses the program based on its array information to get its program iteration number, reallocates the number of threads for different execution modes in OpenMP, and optimizes the thread group increase factor by combining the DCU hardware information to adjust the thread. This paper uses the SPEC ACCEL test set to optimize the number of threads in the DCU. In this paper, we use the SPEC ACCEL test set and Polybench standard test set to test the redistribution of threads and thread groups in two parallel modes using the thread scheduling optimization algorithm. The average speedup ratio of ACCEL was improved by 40%.

Improvement and comparison the performance of fuzzing testing algorithms for applications in Google Thread Sanitizer

It is difficult to imagine modern information systems without the use of multithreading. The use of multithreading can both improve the performance of the system as in whole so as slow down the execution of multithreaded applications due to the occurrence of multithreaded programming errors. To find such errors in C/C++ languages, there exists a Google Thread Sanitizer compiler module. The order of execution of threads can change every time the program is started for execution and can affect the appearance of such errors. To repeatedly change the order of execution of threads during the execution of the program, Google Thread Sanitizer has a fuzzing testing module that allows you to increase the probability of finding errors. But all the thread scheduling algorithms in this module are presented in the form of sequential execution of threads which can lead to a significant slowdown in Google Thread Sanitizer as well as can affect the testing of applications that depends on timers (waiting for network events, deadline for operations, ...). To speed up the work of fuzzing schedulers, a method for parallelizing independent transitions is proposed. From the point of view of multithreaded programming errors, it is only important to change the shared state between threads, and local calculations do not affect the reproduction of multithreaded errors. The changes of shared states themselves occur at synchronization points (places in the code where threads are switched according to the principle of cooperative multitasking). The method suggests ordering only the change of shared states at synchronization points, and performing local calculations in parallel, due to which parallelization is achieved. For the analysis of theoretical complexity of the algorithm, the method of combinatorial counting is used. A new approach to the organization of fuzzing testing based on the method of parallelization of independent transitions is proposed the implementation of which, according to theoretical and practical estimates, shows a noticeable acceleration of the work of fuzzing schedulers. According to the results of the experiment, it was revealed that for the algorithm of iterating through all execution variants, the acceleration of execution reaches 1.25 times for two threads. For an arbitrary number of threads, an estimate is presented in the form of a formula. The proposed approach allows fuzzing tests to cover multithreaded applications for which execution time is important — applications with reference to timers which improve the quality of the software.

Scheduling and thread management with RTEMS

The goal of a real-time operating system (RTOS) is to support real-time and embedded system (RT/ES) application development, which differ from general-purpose applications because of the size, weight, and power (SWaP) and timing constraints imposed by embedded applications. Useful RTOS features include real-time thread scheduling, thread communication, synchronization, interrupt handling, memory management, file systems, device drivers, networking, and debugging support. The Real-Time Executive for Multi-processor Systems (RTEMS) is a free and open-source RTOS that supports over a dozen processor architecture families and over 150 embedded system boards. RTEMS is designed to support embedded applications with stringent real-time requirements while being compatible with open standards such as POSIX. RTEMS includes optional services such as TCP/IP networking and file systems while still offering minimum executable sizes under 20 KB in useful configurations. One of the primary functions of an RTOS is to select threads that can obtain access to resources such as shared memory and processor time. RTEMS uses multiple algorithms to manage both waiting threads and those ready to execute. The thread execution schedulers include the traditional RTOS round robin and deterministic priority schedulers, rate monotonic, earliest deadline first (EDF), constant bandwidth server (CBS), and simple SMP scheduling algorithms. The RTEMS scheduling framework allows the application developer to select the thread scheduling algorithm that best meets the application's space and time requirements. ÂăWe will present how this framework can be used by researchers to integrate their own scheduling algorithm into RTEMS and test it using a scheduling simulator before deploying it on target hardware.

Delivering fairness and priority enforcement on asymmetric multicore systems via OS scheduling

Symmetric-ISA (instruction set architecture) asymmetric-performance multicore processors (AMPs) were shown to deliver higher performance per watt and area than symmetric CMPs for applications with diverse architectural requirements. So, it is likely that future multicore processors will combine big power-hungry fast cores and small low-power slow ones. In this paper, we propose a novel thread scheduling algorithm that aims to improve the throughput-fairness trade-off on AMP systems. Our experimental evaluation on real hardware and using scheduler implementations on a general-purpose operating system, reveals that our proposal delivers a better throughput-fairness trade-off than previous schedulers for a wide variety of multi-application workloads including single-threaded and multithreaded applications.

Analysis of scalable data-privatization threading algorithms for hybrid MPI/OpenMP parallelization of molecular dynamics

We propose and analyze threading algorithms for hybrid MPI/OpenMP parallelization of a molecular-dynamics simulation, which are scalable on large multicore clusters. Two data-privatization thread scheduling algorithms via nucleation-growth allocation are introduced: (1) compact-volume allocation scheduling (CVAS); and (2) breadth-first allocation scheduling (BFAS). The algorithms combine fine-grain dynamic load balancing and minimal memory-footprint data privatization threading. We show that the computational costs of CVAS and BFAS are bounded by Θ(n 5/3 p −2/3) and Θ(n), respectively, for p threads working on n particles on a multicore compute node. Memory consumption per node of both algorithms scales as O(n+n 2/3 p 1/3), but CVAS has smaller prefactors due to a geometric effect. Based on these analyses, we derive the selection criterion between the two algorithms in terms of the granularity, n/p. We observe that memory consumption is reduced by 75 % for p=16 and n=8,192 compared to a naïve data privatization, while maintaining thread imbalance below 5 %. We obtain a strong-scaling speedup of 14.4 with 16-way threading on a four quad-core AMD Opteron node. In addition, our MPI/OpenMP code achieves 2.58× and 2.16× speedups over the MPI-only implementation on 32,768 cores of BlueGene/P for 0.84 and 1.68 million particle systems, respectively.

Dynamic thermal management by greedy scheduling algorithm

Chip multiprocessors (CMPs) allow thread level parallelism, thus increasing performance. However, this comes with the cost of temperature problem. CMPs require more power, creating non uniform power map and hotspots. Aiming at this problem, a thread scheduling algorithm, the greedy scheduling algorithm, was proposed to reduce the thermal emergencies and to improve the throughput. The greedy scheduling algorithm was implemented in the Linux kernel on Intel's Quad-Core system. The experimental results show that the greedy scheduling algorithm can reduce 9.6%−78.5% of the hardware dynamic thermal management (DTM) in various combinations of workloads, and has an average of 5.2% and up to 9.7% throughput higher than the Linux standard scheduler.

Performance enhancement of real‐time computing for small unmanned helicopter autopilot

PurposeThe purpose of this paper is to make performance improvements and timely critical execution enhancements for operational flight program (OFP). The OFP is core software of autonomous control system of small unmanned helicopter.Design/methodology/approachIn order to meet the time constraints and enhance control application performance, two major improvements were done at real‐time operating system (RTOS) kernel. They are thread scheduling algorithm and lock‐free thread message communication mechanism. Both of them have a direct relationship with system efficiency and indirect relationship with helicopter control application execution stability through improved deadline keeping characteristics.FindingsIn this paper, the suitability of earliest deadline first (EDF) scheduling algorithm and non‐blocking buffer (NBB) mechanism are illustrated with experimental and practical applications. Results of this work show that EDF contributes around 15 per cent finer‐timely execution and NBB enhances kernel's responsiveness around 35 per cent with respect to the number of thread context switch and CPU utilization. These apply for OFP implemented over embedded configurable operating system (eCos) RTOS on x86 architecture‐based board.Practical implicationsThis paper illustrates an applicability of deadline‐based real‐time scheduling algorithm and lock‐free kernel communication mechanism for performance enhancement and timely critical execution of autonomous unmanned aerial vehicle control system.Originality/valueThis paper illustrates a novel approach to extend RTOS kernel modules based on unmanned aerial vehicle control application execution scenario. Lock‐free thread communication mechanism is implemented, and tested for applicability at RTOS. Relationship between UAV physical and computation modules are clearly illustrated via an appropriate unified modelling language (UML) collaboration and state diagrams. As experimental tests are conducted not only for a particular application, but also for various producer/consumer scenarios, these adequately demonstrate the applicability of extended kernel modules for general use.

Recovering from distributable thread failures in distributed real-time Java

We consider the problem of recovering from the failures of distributable threads (“threads”) in distributed real-time systems that operate under runtime uncertainties including those on thread execution times, thread arrivals, and node failure occurrences. When a thread experiences a node failure, the result is a broken thread having an orphan. Under a termination model, the orphans must be detected and aborted, and exceptions must be delivered to the farthest, contiguous surviving thread segment for resuming thread execution. Our application/scheduling model includes the proposed distributable thread programming model for the emerging Distributed Real-Time Specification for Java (DRTSJ), together with an exception-handler model. Threads are subject to time/utility function (TUF) time constraints and an utility accrual (UA) optimality criterion. A key underpinning of the TUF/UA scheduling paradigm is the notion of “best-effort” where higher importance threads are always favored over lower importance ones, irrespective of thread urgency as specified by their time constraints. We present a thread scheduling algorithm called HUA and a thread integrity protocol called TPR. We show that HUA and TPR bound the orphan cleanup and recovery time with bounded loss of the best-effort property. Our implementation experience for HUA/TPR in the Reference Implementation of the proposed programming model for the DRTSJ demonstrates the algorithm/protocol's effectiveness.

네트워크 프로세서를 위한 다중 쓰레드 스케줄링

본 논문은 다중 프로세서(Multiprocessor) 기반 다중 쓰레드(Multithreaded) 구조의 네트워크 프로세서를 이용한 패킷 치리 시스템에서 패킷을 보다 고속으로 처리하기 위한 쓰레드 스케줄링 기법을 제안한다 이를 위하여 스케줄링과 관련한 인자를 실험을 통하여 얻고, 패킷 내용 및 다중 쓰레드 아키텍쳐를 표현하는 인자를 포함하도록 설계하였다. 시뮬레이터를 이용한 실험을 통하여 제안된 스케줄링 기법이 제공하는 처리율 및 부하 분산 정도가 다른 스케줄링 기법과 비교하여 효율적임을 증명하였다. In this paper, we propose a thread scheduling algorithm for faster packet processing on the network processors with multithreaded multiprocessor architecture. To implement the proposed algorithm. we derived several basic parameters related to the thread scheduling and included a new parameter representing the packet contents and the multithreaded architecture. Through the empirical study using a simulator, we proved the proposed scheduling algorithm provides better throughput and load balancing compared to the general thread scheduling algorithm.

The Performance Implications of Locality Information Usage in Shared-Memory Multiprocessors

Large caches used in scalable shared-memory architectures can avoid high memory access time only if data is referenced within the address scope of the cache. Consequently, locality is the key issue in multiprocessor performance. While CPU utilization still determines scheduling decisions of contemporary schedulers, we propose novel scheduling policies based on locality information derived from cache miss counters. A locality-conscious scheduler can reduce the costs for reloading the cache after each context switch. Thus, the potential benefit of using locality information increases with the frequency of scheduling decisions. Lightweight threads have become a common abstraction in the field of programming languages and operating systems. User-lever schedulers make frequent context switches affordable and therefore draw most profit from the usage of locality information if the lifetime of cachelines exceeds scheduling cycles. This paper examines the performance implications of locality information usage in thread scheduling algorithms for scalable shared-memory multiprocessors. A prototype implementation shows that a locality-conscious scheduler outperforms approaches ignoring locality information.