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Twitch 用 VP9 直播...

Twitch 整理了一篇「How VP9 delivers value for Twitch’s esports live streaming」,說明他們用 VP9 的經驗談。

裡面有很大的篇幅是在講 VP9 與 H.264 的比較,不過這兩個用的技術就已經不是同一個年代了,沒有進步的話就不用出來玩了...

裡面有講到一些有趣的東西,像是提到是用 FPGA 即時壓縮:

In this article, we will show that the FPGA-based real-time VP9 encoding can deliver at least 25% bitrate savings compared to the highest-quality H.264 encoders deployed in Twitch’s production today.

然後提到 1080p60 至少省了 25% 的頻寬 (這邊應該是相較於 H.264):

VP9’s Compression Efficiency for Live 1080p60 Encoding: We Can Achieve At Least 25% Bitrate Savings

查了一下,在桌機上的瀏覽器都差不多支援了:

VP9 is implemented in these web browsers:

Chromium and Google Chrome (usable by default since version 29 from May and August 2013, respectively),
Opera (since version 15 from July 2013),
Mozilla Firefox (since version 28 from March 2014),
Microsoft Edge (as of summer 2016).

行動裝置的話 Android 4.4+ 有支援,但在 iOS 上沒有支援...

整體看起來普及率算是不低,可以引入當主力 codec 降低頻寬成本,當設備不支援 VP9 時 (應該只有 iOS 透過 Safari 觀看的情況) 就用 H.264 stream 提供服務。

Fortnite 看起來沒上 Auto Scaling?(或是沒正確設好?)

Fortnite 遊戲的伺服器放在 AWS 上,看起來這波 Meltdown 的安全更新 (KPTI) 造成非常大的 overhead:

不過看起來出了問題:

We wanted to provide a bit more context for the most recent login issues and service instability. All of our cloud services are affected by updates required to mitigate the Meltdown vulnerability. We heavily rely on cloud services to run our back-end and we may experience further service issues due to ongoing updates.

最有可能的是把 AWS 當作一般的 VPS 在用,另外一種可能是有部份內部服務沒有 scale,造成上了 KPTI 後 overhead 增加,就卡住了...

在 TeX 上輸出圍棋棋譜的套件 psgo_emitter

忘記是在哪邊看到 avysk/psgo_emitter 這個套件,提供 TeX 語法輸出成圍棋棋盤的圖示,不過說明裡說只支援 Windows 平台:

psgo_emitter is a (Windows) console utility to create go diagrams for go life-and-death problems (tsumego).

可以只輸出角部,像是這段語法:

    \begin{psgopartialboard}{(1,1)(8,6)}
            \stone{black}{b}{3}
            \stone{black}{d}{3}
            \stone{black}{b}{4}
            \stone{white}{d}{5}
            \stone{white}{g}{2}
            \stone{black}{d}{2}
            \stone{white}{b}{5}
            \stone{white}{c}{4}
            \stone{white}{e}{4}
            \stone{white}{e}{3}
            \stone{white}{e}{2}
            \stone{black}{e}{1}
    \end{psgopartialboard}

會輸出這樣的圖:

另外也可以把手順放進去:

    \begin{psgopartialboard}{(1,1)(8,6)}
            \stone{black}{b}{3}
            \stone[\marklb{1}]{black}{a}{2}
            \stone{black}{d}{3}
            \stone{black}{b}{4}
            \stone[\marklb{8}]{white}{f}{1}
            \stone[\marklb{6}]{white}{d}{1}
            \stone{white}{e}{2}
            \stone{white}{g}{2}
            \stone{black}{d}{2}
            \stone{white}{b}{5}
            \stone[\marklb{7}]{black}{b}{2}
            \stone[\marklb{9}]{black}{a}{1}
            \stone{white}{c}{4}
            \stone[\marklb{4}]{white}{c}{2}
            \stone{white}{e}{4}
            \stone[\marklb{5}]{black}{c}{3}
            \stone{white}{e}{3}
            \stone[\marklb{2}]{white}{b}{1}
            \stone{white}{d}{5}
            \stone[\marklb{3}]{black}{a}{4}
            \stone{black}{e}{1}
    \end{psgopartialboard}

就會輸出:

套件還很新,不知道之後會發展成什麼樣子...

各種道路設計對於流量的影響?

在「The rates of traffic flow on different kinds of 4-way intersections」這邊看到有趣的東西,利用遊戲 Cities: Skylines 模擬各種道路設計對流量的影響:

This is an animation of traffic flows simulated on 30 different kinds of four-way junctions, from two roads intersecting with no traffic lights or signs to complex stacked interchanges that feature very few interactions between individual cars. It was recorded in a game called Cities: Skylines, a more realistic take on SimCity.

影片在這:

記得這是模擬,實際情況會有其他考量,所以裡面的結果參考就好...

然後裡面有看到很多常見的設計,還有一些沒看過的神奇設計 XD 另外有些設計超級複雜,第一次開的人真的會知道怎麼開嗎 XDDD

AlphaGo 的開局庫分析

Facebook 上看到 Aja Huang 的訊息,介紹了 DeepMind 放出的新資料,由 AlphaGo 分析人類開局的各種勝率 (不是先前發表出來更凶的 AlphaZero,但不曉得是 AlphaGo Zero 還是 AlphaGo Master...)。

網站在 AlphaGo Teach: Discover new and creative ways of playing Go,盤面上的數字都是指黑棋勝率。

This tool provides analysis of 6,000 of the most popular opening sequences from the recent history of Go, using data from 231,000 human games and 75 games AlphaGo played against human players.

Explore the board and learn how AlphaGo's moves compare to those of professional and amateur players.

由於這是暴力法算出超大量的開局資料,而且是完整公佈在網路上,可以預料接下來的職業比賽,開局應該會參考這邊的資料進行修正...

Steam 停止使用 Bitcoin 購買遊戲

Steam 宣佈停止使用 Bitcoin 購買遊戲:「Steam is no longer supporting Bitcoin」。

官方提到的原因是因為交易費用太高 (雖然是讓使用者付):

In the past few months we've seen an increase in the volatility in the value of Bitcoin and a significant increase in the fees to process transactions on the Bitcoin network. For example, transaction fees that are charged to the customer by the Bitcoin network have skyrocketed this year, topping out at close to $20 a transaction last week (compared to roughly $0.20 when we initially enabled Bitcoin).

另外一個原因是波動問題:

Historically, the value of Bitcoin has been volatile, but the degree of volatility has become extreme in the last few months, losing as much as 25% in value over a period of days.

所以這樣推測,Steam 不是直接換成法幣?我記得他們合作的交易所 (BitPay) 可以馬上換成法幣...

AlphaGo Zero 演算法的 Open Source 實做

Leela 的作者 Gian-Carlo Pascutto 依照 paper 的描述寫完了,放在 GitHub 上的 gcp/leela-zero

不過他在 Twitter 上也提到了,open source 實做不是真正的困難,真正的困難在於訓練完的資料,那個部份需要大量的成本才有辦法作到:

另外他推估 AlphaGo Zero 的計算量是 1700 年 (以 1080 Ti 來計算):「[Computer-go] Zero performance」。

另外 Leela 0.11.0 也推出了,還是先維持 policy + value 的方式,但引入了不少新演算法加強。另外一個蠻特別的地方是 Windows 版改用 clang 而變快不少:

Windows version is now compiled with Clang/LLVM 5.0 instead of MSVC2017. This makes the Monte Carlo evaluations about 15% faster.

雖然 DeepMind 說要收手,但還是留下不少方向讓大家走...

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