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| 日期 | 订阅者增长 | 提及 | 频道 | |
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频道帖子
| 2 | How fast is Python 3.15?
Comments
via blog.miguelgrinberg.com via gnyeki | 71 |
| 3 | Reasons to dislike AI coding
Comments
via sicpers.info via j11g | 71 |
| 4 | OpenAI shares mathematics research catalogue
Comments
via github.com via bkruger | 103 |
| 5 | When random is not actually random enough
Comments
via ersc.io via fanf | 132 |
| 6 | Raspberry Pi Desktop now available for PC and Mac
Comments
via raspberrypi.com via bt | 126 |
| 7 | Burn 0.22.0: Faster Builds, Easier Extensions, and Smarter Autotuning
Comments
via tracel.ai via nrposner | 118 |
| 8 | Is COSMIC DE mogging KDE Plasma?
Comments
via thelibre.news via edwardloveall | 130 |
| 9 | Janet on x32: 32-bit Pointers, 64-bit Speed, 25% Less RAM
Comments
via alexalejandre.com via veqq | 168 |
| 10 | How to fix a bug in a fix
Comments
via projectzero.google via freddyb | 158 |
| 11 | A Terminal Protocol for Program Status (OSC 7501)
Comments
via mitchellh.com via lalitm | 148 |
| 12 | That Time I Worked With a Laptop Thief
Comments
via blog.pipetogrep.org via jeanthomas | 164 |
| 13 | A sustainable web career, for when all this blows over
Comments
via dbushell.com via nrvous | 170 |
| 14 | Pared - remove unwanted Apple Intelligence models without disabling SIP
Comments
via github.com by FlameFlag | 165 |
| 15 | Inside the Windows I/O Manager: Deep dive into how read I/O requests are initialized
Comments
via winware31.blogspot.com via calvin | 146 |
| 16 | Brut, the Brutal Router for Unix Tools
Comments
via brut.sh by sstephenson | 158 |
| 17 | Why We Should Inject Dependencies
Comments
via gist.github.com via PuercoPop | 151 |
| 18 | Last rites for Gentoo's Chromium package
Comments
via lwn.net via calvin | 140 |
| 19 | Perseus: A Fail-Slow Detection Framework for Cloud Storage Systems (2023)
Abstract: The newly-emerging “fail-slow” failures plague both software and hardware where the victim components are still functioning yet with degraded performance. To address this problem, this paper presents PERSEUS, a practical fail-slow detection framework for storage devices. PERSEUS leverages a light regression-based model to fast pinpoint and analyze fail-slow failures at the granularity of drives. Within a 10-month close monitoring on 248K drives, PERSEUS managed to find 304 fail-slow cases. Isolating them can reduce the (node-level) 99.99th tail latency by 48%. We assemble a large-scale fail-slow dataset (including 41K normal drives and 315 verified fail-slow drives) from our production traces, based on which we provide root cause analysis on fail-slow drives covering a variety of ill-implemented scheduling, hardware defects, and environmental factors. We have released the dataset to the public for fail-slow study.Comments
via usenix.org via typesanitizer | 142 |
| 20 | Chrome's Response to Recent ccTLD Registry Hijacks
Comments
via blog.google via agwa | 141 |
