Shards on a Shoestring: 商品硬件上NEAR协议Nightshade分片的实证表征

中文摘要 AI 辅助

NEAR协议的Nightshade架构旨在通过对状态和计算进行水平分片，实现每秒一百万笔交易（TPS）。已发表的基准测试是在昂贵的谷歌云平台基础设施上进行的，每小时成本约700美元，这给学术研究留下了显著的可复现性差距。我们首次在商品硬件上对NEAR Nightshade分片进行了独立的实证表征：一台Chameleon Cloud裸金属节点，配备48个超线程Intel Xeon核心、128GB内存和80–100MB/s的HDD存储。我们系统地将分片数量从N=1扫描到N=24，测量聚合TPS、每分片TPS、区块时间、BFT最终性、内存和磁盘I/O。我们识别出三个不同的瓶颈区间：低N时的L3缓存压力、中N时的见证人八卦管道饱和，以及高N时的连贯性崩溃。一个关键的意外发现是，HDD写入延迟充当了见证人八卦管道的隐式流量控制。通过RAM支持的tmpfs移除它会导致N=16时链完全停滞，孤儿见证人率在47% CPU利用率下出现29倍的飙升。聚合TPS在N=8时达到峰值（比N=1高40%），随后逆转，到N=24时每分片TPS崩溃23倍。我们的数据集为配套的SimPy分片模拟器提供了首个商品硬件校准基线。

英文摘要

NEAR Protocol's Nightshade architecture targets one million transactions per second (TPS) through horizontal sharding of both state and computation. Published benchmarks were produced on expensive Google Cloud Platform infrastructure costing approximately \$700 per hour, leaving a significant reproducibility gap for academic research. We present the first independent empirical characterization of NEAR Nightshade sharding on commodity hardware: a Chameleon Cloud bare-metal node with 48 hyperthreaded Intel Xeon cores, 128\,GB RAM, and HDD storage at 80--100\,MB/s. We systematically sweep shard count from $N{=}1$ to $N{=}24$, measuring aggregate TPS, per-shard TPS, block time, BFT finality, memory, and disk I/O. We identify three distinct bottleneck regimes: L3 cache pressure at low $N$, witness gossip pipeline saturation at mid $N$, and coherence collapse at high $N$. A key unexpected finding is that HDD write latency acts as implicit flow control for the witness gossip pipeline. Removing it via RAM-backed tmpfs causes complete chain stall at $N{=}16$, with a 29$\times$ spike in orphan witness rate at 47\% CPU utilization. Aggregate TPS peaks at $N{=}8$ (+40\% over $N{=}1$) then reverses, with per-shard TPS collapsing 23$\times$ by $N{=}24$. Our dataset provides the first commodity-hardware calibration baseline for the companion SimPy sharding simulator.

发表机构

• Illinois Institute of Technology（伊利诺伊理工学院）

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