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1 Markets I: The Ecosystem and Exchange-Traded Marketsالأسواق عبر الإنترنت 2 Markets II: Rates, FX and Creditالأسواق عبر الإنترنت 3 Markets III: Commodities, Energy and Cryptoالأسواق عبر الإنترنت 4 Quantitative Methodsالأساليب عبر الإنترنت 5 Derivatives and Volatilityالمشتقات عبر الإنترنت 6 Rates, Credit, XVA and Riskالفائدة والائتمان والمخاطر عبر الإنترنت 7 Research Craft: Predictors, Backtests, Measurement, Portfoliosالبحث عبر الإنترنت 8 Strategies I: Equities and Futuresالاستراتيجيات عبر الإنترنت 9 Strategies II: Volatility, Relative Value, Macro and the Bank Desksالاستراتيجيات عبر الإنترنت 10 Microstructure and Executionالتنفيذ عبر الإنترنت 11 Market Making and High-Frequency Tradingصناعة السوق عبر الإنترنت 12 Machine Learning for Marketsتعلم الآلة عبر الإنترنت 13 Low-Latency Softwareالتكنولوجيا عبر الإنترنت 14 Networks, Hardware and Trading Infrastructureالتكنولوجيا عبر الإنترنت 15 Research, Data and Risk Platformsالتكنولوجيا عبر الإنترنت 16 The Desk and the Firmالشركة عبر الإنترنت 17 The Industry: Firms, Roles and Careersالمسارات المهنية عبر الإنترنت 18 The Interview Bookالمسارات المهنية عبر الإنترنت
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Quantitative Finance · المسرد

ما معنى CPU steal time, noisy neighbour؟

يُعرف أيضًا باسم: CPU steal time · noisy neighbour

Definition 16.7 Networks, Hardware and Trading Infrastructure · الفصل 16 — Trading in a Public Cloud

CPU steal time is the time a virtual CPU was ready to run but the hypervisor ran something else on the physical CPU; Linux reports it as “involuntary wait”. A noisy neighbour is another tenant of the same physical server or network whose load takes resources (CPU, cache, memory bandwidth, network queues) from a customer’s machine and so adds delay to it.

Casep50p90p99p99.9p99.99
Same zone (published)270–395–760
Same zone (model)270333396463743
Cross zone (published)555–755–1 905
Cross zone (model)5556577558511 908
Shared host, noisy neighbour (model)2703334007 47413 940
Table 16.1. Round-trip percentiles in microseconds: the published measurement (Hilyard et al., AWS, same subnet and cross AZ) and the simulation that firm.cloudplan fits to it; the noisy-neighbour case is an assumption. Data: nw_cloud.percentiles().
Simulation fitted to a published measurement: round-trip percentiles within a zone and across zones, and on a shared host with an assumed noisy neighbour. Crossing a zone doubles the body of the distribution; a noisy neighbour leaves the body alone and multiplies the tail. Data: fig_cloud.py.
Figure 16.3. Simulation fitted to a published measurement: round-trip percentiles within a zone and across zones, and on a shared host with an assumed noisy neighbour. Crossing a zone doubles the body of the distribution; a noisy neighbour leaves the body alone and multiplies the tail. Data: fig_cloud.py.
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