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Wed, 22 Apr 2026 11:49:17 -0700 (PDT) Received: from biancapradeep.lan ([2605:a601:8130:9800::9]) by smtp.gmail.com with ESMTPSA id 6a1803df08f44-8b02ae5c4b9sm183657196d6.28.2026.04.22.11.49.16 (version=TLS1_3 cipher=TLS_AES_256_GCM_SHA384 bits=256/256); Wed, 22 Apr 2026 11:49:17 -0700 (PDT) From: Bhithashri385 To: linux-kernel@vger.kernel.org Cc: tj@kernel.org Subject: Re: workqueue: introduce cache_shard_size Date: Wed, 22 Apr 2026 14:49:09 -0400 Message-ID: <20260422184913.25652-1-bojanalahithashri@gmail.com> X-Mailer: git-send-email 2.47.0 In-Reply-To: <283d252c7356bdc7640f48ef716051cb@kernel.org> References: Precedence: bulk X-Mailing-List: linux-kernel@vger.kernel.org List-Id: List-Subscribe: List-Unsubscribe: MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Hi, I did a quick sanity check of cache_shard_size on a dual-socket system: * 2x28C/56T (112 CPUs total), x86_64 * single local NVMe (XFS) * upstream kernel with this change Workload: fio, 4k buffered writes with fsync=1 numjobs = 56 / 112 / 168 Compared: workqueue.cache_shard_size=1 vs 8 Results (IOPS / BW): jobs=56: shard=1: ~265k IOPS, ~1035 MiB/s shard=8: ~276k IOPS, ~1078 MiB/s jobs=112: shard=1: ~248k IOPS, ~968 MiB/s shard=8: ~241k IOPS, ~941 MiB/s jobs=168: shard=1: ~234k IOPS, ~912 MiB/s shard=8: ~233k IOPS, ~909 MiB/s fsync latency (avg): jobs=56: shard=1: ~33 us shard=8: ~28 us jobs=112: shard=1: ~53 us shard=8: ~47 us jobs=168: shard=1: ~279 us shard=8: ~256 us Observations: * Small improvement (~4%) at moderate concurrency (56 jobs). * Differences mostly disappear at higher concurrency; both configs converge once the device is saturated (~93–96% util). * fsync latency is consistently a bit lower with sharding. Interpretation: This workload appears to become device-bound quickly, so the benefit from reduced workqueue contention is limited. The small gain at moderate load and lower fsync latency suggest sharding is helping somewhat before hitting the storage bottleneck. I haven't tried multi-device or more metadata-heavy workloads yet, which may stress workqueues more directly. Thanks, Hithashree