Performance evaluation of scheduling tasks in many-core systems utilizing processes and threads

Mejgan Dedaj; Argyro Gailla; Theofanis Ioannou; Stamatia Kastrinaki; Hermione Kimpouropoulou; Dimitrios Kontodimos; Kleopatra Kontogianni; Sotirios Kontogiannis; Michail Panagiotidis Kannas; Anastasia Papouda; Anna Maria Sidiropoulou; George Tavridis

arXiv · 2607.04821

Performance evaluation of scheduling tasks in many-core systems utilizing processes and threads

Mejgan Dedaj·Argyro Gailla·Theofanis Ioannou·Stamatia Kastrinaki·Hermione Kimpouropoulou·Dimitrios Kontodimos·Kleopatra Kontogianni·Sotirios Kontogiannis·Michail Panagiotidis Kannas·Anastasia Papouda·Anna Maria Sidiropoulou·George Tavridis

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Abstract

This study assesses the scalability of process-based and thread-based schedulers for many-core shared-memory systems using a memory-intensive row-wise quick-sort workload on large three-dimensional tensors. The process-based evaluation considers bounded prolific, bounded collective, and three pipe-based producer-consumer schedulers: one-to-one, one-to-many, and many-to-many. These pipe schedulers dynamically stream task identifiers to worker processes, exchanging increased inter-process communication overhead for enhanced runtime load balancing and flexible chunk-based task dispatching. The thread-based evaluation examines static, dynamic, guided, chunk-based, chunk-stealing, adaptive chunk, and AIMD adaptive scheduling strategies. The AIMD scheduler employs an additive-increase multiplicative-decrease policy inspired by TCP congestion control, utilizing an exponentially weighted moving average (EWMA) of CPU utilization to regulate a contention window that limits the number of concurrently active chunks. The adaptive chunk scheduler further modifies chunk size based on observed per-thread execution speed. Experimental results on a 24-core x86-64 platform indicate that thread schedulers deliver the highest overall performance, with dynamic and guided scheduling yielding the most favorable practical outcomes. Among process schedulers, pipe-based designs demonstrate the strongest scalability, with one-to-one pipes excelling for smaller workloads and many-to-many pipes preferred for larger workloads. In summary, lightweight thread scheduling is optimal for shared-memory row sorting, while AIMD/adaptive scheduling and pipe-based process scheduling remain valuable for contention-aware execution, explicit inter-process coordination, and distributed-style heterogeneous workload management.

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Mejgan Dedaj, Argyro Gailla, Theofanis Ioannou, Stamatia Kastrinaki, Hermione Kimpouropoulou, Dimitrios Kontodimos, Kleopatra Kontogianni, Sotirios Kontogiannis, Michail Panagiotidis Kannas, Anastasia Papouda, Anna Maria Sidiropoulou, George Tavridis. 2026-07-06. Performance evaluation of scheduling tasks in many-core systems utilizing processes and threads. https://arxiv.org/abs/2607.04821

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