{"ID":5937192,"CreatedAt":"2026-07-07T03:14:33.014478982Z","UpdatedAt":"2026-07-09T08:41:17.711438627Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.04821","arxiv_id":"2607.04821","title":"Performance evaluation of scheduling tasks in many-core systems utilizing processes and threads","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.","short_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-consum...","url_abs":"https://arxiv.org/abs/2607.04821","url_pdf":"https://arxiv.org/pdf/2607.04821v1","authors":"[\"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\"]","published":"2026-07-06T08:52:20Z","proceeding":"cs.DC","tasks":"[\"cs.DC\",\"cs.PF\"]","methods":"[]","has_code":false}