[TENT] Proxy manager performance optimization#2091
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- Add comprehensive performance monitoring (ProxyManagerMetrics) - Optimize staging buffer configuration (4MB chunks, 64 count) - Implement intelligent retry mechanism for remote staging failures - Fix event queue handling consistency in INFLIGHT_REMOTE state - Add performance metrics: throughput, latency, retry counts, parallelism - Improve error handling with configurable retry logic (default: 3 attempts) Performance improvements: - Better pipeline parallelism with 4-buffer circulation - Reduced latency through async remote staging operations - Enhanced reliability through smart retry mechanism - Improved observability through detailed metrics collection Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
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Code Review
This pull request introduces a metrics tracking system and a retry mechanism for remote staging within the ProxyManager. The new ProxyManagerMetrics struct tracks transfers, data volume, latency, and retry attempts. Feedback focuses on addressing a potential resource leak where in-flight batches are not freed during failures, correcting the throughput calculation to account for parallel execution using wall-clock time, and ensuring metrics accurately reflect successful transfers by updating them at the end of the process. Additionally, the pipeline_parallel_chunks metric was flagged as redundant or logically inconsistent.
| auto& fut = remote_futures[id]; | ||
| if (!fut.valid()) { | ||
| chunk.state = StageState::FAILED; | ||
| event_queue.push(id); |
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This call triggers the StageState::FAILED case, which returns an error immediately. However, the current implementation of the FAILED case (line 432) does not free any in-flight batches stored in the chunks vector. This leads to a resource leak in the TransferEngineImpl. Before returning an error, the loop should ensure all allocated batches for all chunks are freed.
| double getThroughputGBps() const { | ||
| uint64_t us = total_latency_us.load(); | ||
| return us > 0 ? (total_bytes_transferred.load() / 1e9) / (us / 1e6) | ||
| : 0.0; | ||
| } |
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The throughput calculation (total_bytes_transferred.load() / 1e9) / (us / 1e6) is based on the sum of latencies of all transfers. In a parallel execution environment with multiple shards, this sum grows faster than wall-clock time, meaning the metric represents the average throughput per stream rather than the aggregate system throughput. To measure system-wide throughput, you should track the wall-clock time since the metrics were last reset.
| metrics_.total_transfers.fetch_add(1, std::memory_order_relaxed); | ||
| metrics_.total_bytes_transferred.fetch_add(request.length, | ||
| std::memory_order_relaxed); |
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Updating total_transfers and total_bytes_transferred at the start of the function counts transfers that may eventually fail. It is more accurate to update these metrics at the end of the function, only after the transfer has successfully completed. This also ensures consistency with the total_latency_us metric which is updated at the end.
| metrics_.pipeline_parallel_chunks.fetch_add(kStageBuffers, | ||
| std::memory_order_relaxed); |
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The pipeline_parallel_chunks metric is incremented by a constant kStageBuffers (4) for every successful transfer, making it redundant with total_transfers. If the intent is to track the total number of chunks processed, it should use chunks.size(). If the intent is to track parallelism, a counter is not the appropriate metric type.
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Description
This PR focuses specifically on ProxyManager performance optimization based on the revise-paper-branch implementation, delivering significant throughput improvements, latency reduction, and enhanced reliability through intelligent retry mechanisms.
Module
mooncake-transfer-engine)mooncake-store)mooncake-ep)mooncake-integration)mooncake-p2p-store)mooncake-wheel)mooncake-pg)mooncake-rl)Type of Change
How Has This Been Tested?
Checklist
./scripts/code_format.shbefore submitting.