Heuristic-based Task-to-Thread Mapping in Multi-Core Processors

Gharajeh, Mohammad Samadi; Royuela, Sara; Pinho, Luís Miguel; Carvalho, Tiago; Quiñones, Eduardo

doi:10.1109/etfa52439.2022.9921453

Cited by 5 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach aims to automate the mapping selection, enhance the predictability and robustness of the mapping, minimize the response time of the application, and reduce the running time overhead of the mapping process. This phase uses a simulation approach to explore different mapping algorithms, using the heuristic-based mapping approach designed by Gharajeh et al [9]. This approach separates the mapping into two phases: scheduling and allocation.…”

Section: A Design-space Exploration Of Static Mappingmentioning

confidence: 99%

Framework for the Analysis and Configuration of Real-Time OpenMP Applications

Carvalho,

Pinho,

Samadi

et al. 2023

2023 IEEE 21st International Conference on Industrial Informatics (INDIN)

View full text Add to dashboard Cite

High-performance cyber-physical applications impose several requirements with respect to performance, functional correctness and non-functional aspects. Nowadays, the design of these systems usually follows a model-driven approach, where models generate executable applications, usually with an automated approach. As these applications might execute in different parallel environments, their behavior becomes very hard to predict, and making the verification of non-functional requirements complicated. In this regard, it is crucial to analyse and understand the impact that the mapping and scheduling of computation have on the real-time response of the applications. In fact, different strategies in these steps of the parallel orchestration may produce significantly different interference, leading to different timing behaviour.Tuning the application parameters and the system configuration proves to be one of the most fitting solutions. The design space can however be very cumbersome for a developer to test manually all combinations of application and system configurations. This paper presents a methodology and a toolset to profile, analyse, and configure the timing behaviour of highperformance cyber-physical applications and the target platforms. The methodology leverages on the possibility of generating a task dependency graph representing the parallel computation to evaluate, through measurements, different mapping configurations and select the one that minimizes response time.

show abstract

Section: A Design-space Exploration Of Static Mappingmentioning

confidence: 99%

Framework for the Analysis and Configuration of Real-Time OpenMP Applications

Carvalho,

Pinho,

Samadi

et al. 2023

2023 IEEE 21st International Conference on Industrial Informatics (INDIN)

View full text Add to dashboard Cite

show abstract

“…The majority of existing research efforts focus on high-level abstractions, neglecting the lower end of the cloud stack, such as the Operating System (OS) layer [10]. In parallel and distributed cloud components, this leads to a general lack of integration with low-level mechanisms, such as tuned scheduling policies [9], [13], [22] or efficient synchronization constructs beyond traditional lock-based primitives, or contention control techniques [25]. Nonetheless, industrial-grade database software often employs low-level optimizations to fully exploit the capabilities of modern many-core machines.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Inducing Huge Tail Latency on a MongoDB deployment

Andreoli,

Cucinotta

2023

2023 IEEE International Conference on Cloud Engineering (IC2E)

View full text Add to dashboard Cite

The NoSQL paradigm has emerged as the leading design choice for cloud providers offering highly scalable storage services. Contrary to traditional relational databases, NoSQL architectures are capable of ingesting the ever-growing volume of nowadays' data-driven applications characterized by low-latency and high-throughput requirements. However, it is difficult to build an ultra-scalable, high-performance storage engine that can sustain an arbitrary number of concurrent clients. A common technique to increase throughput is minimizing the OS overhead, quantified as the number of context switches, through busy waiting (or "spinning"). While this simple synchronization mechanism proves to be beneficial in the high-performance computing community, it requires special care to avoid wasting resources and counter-intuitive behaviors. In this paper, we address an instance of "unsafe" busy waiting in WiredTiger, the underlying storage engine of MongoDB, which leads to a consistent, excessive increase of tail latency in high contention scenarios.

show abstract