diff --git a/.jules/bolt.md b/.jules/bolt.md new file mode 100644 index 0000000..c137d48 --- /dev/null +++ b/.jules/bolt.md @@ -0,0 +1,3 @@ +## 2024-05-18 - Sliding Window Concurrency +**Learning:** In Swift structured concurrency, when processing high-volume tasks using `withTaskGroup`, static chunking (e.g., `stride(from:to:by:)`) limits throughput due to tail latency (waiting for the slowest task in a chunk). +**Action:** Use a sliding window approach with an iterator instead to maintain maximum concurrent execution limits continuously. diff --git a/Sources/Cacheout/Memory/ProcessMemoryScanner.swift b/Sources/Cacheout/Memory/ProcessMemoryScanner.swift index 3f8e728..15b5d68 100644 --- a/Sources/Cacheout/Memory/ProcessMemoryScanner.swift +++ b/Sources/Cacheout/Memory/ProcessMemoryScanner.swift @@ -97,30 +97,35 @@ actor ProcessMemoryScanner { /// /// Returns the collected entries and the count of EPERM failures. private func scanPIDs(_ pids: [pid_t]) async -> (entries: [ProcessEntryDTO], epermCount: Int) { - // Chunk PIDs to cap concurrency at maxConcurrency. - let chunks = stride(from: 0, to: pids.count, by: maxConcurrency).map { - Array(pids[$0..