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ue4 gpu构建_待在家里吗为什么不构建GPU Box！

發布時間：2023/12/15 编程问答 32 豆豆

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ue4 gpu構建

After working with Machine Learning applications for a while, I was excited to try some Deep Leaning models. Probably the biggest obstable that I faced in getting started was the workflow, specifically, finding an accessible, fluid GPU-powered environment to work in. My Mac Pro (affectionately called the trash can model) was not going to help. I began to use cloud services, but missed having my own place to store data and run code without having the meter running. So I decided to build my own GPU box. At first it was pretty Intimidating (capital I), but things went fairly smoothly, and the end result was extremely gratifying. In case my adventure is interesting or helpful to you, here it is!

在使用機器學習應用程序一段時間后，我很高興嘗試一些深度學習模型。我可能在入門中遇到的最大障礙是工作流程，特別是尋找一個可訪問的，具有流暢GPU的環境來工作。我的Mac Pro(完全稱為垃圾桶模型)將無濟于事。我開始使用云服務，但是卻錯過了自己的地方來存儲數據和運行代碼，而無需運行電表。因此，我決定構建自己的GPU盒。剛開始時，這是非常令人生畏的(資本I)，但是事情進展得很順利，最終結果令人非常滿意。萬一我的冒險對您有幫助或對您有幫助，就在這里！

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母板 (Motherboard)

ASUS ROG Strix B360-I

華碩ROG Strix B360-I

I’ll start with the mobo. Let me say upfront that this build won’t apply without modification to your situation if you want to use multiple GPUs. I decided to build a mini-ITX form factor (i.e. small) machine with a single GPU because this was my first build and I thought it would be challenging enough. Also, I like my house to have a decorated and put-together feel, including my office. I wasn’t trying to create a man cave gaming paradise with a large neon-glowing tower. But can I say, I love this board! For the gamers, this was the only RGB item I bought for the system, and it’s perfect. But in practical building terms, the real bonus is the built-in I/O shield. As one of the helpful youtube gaming computer assembly gentlemen pointed out, installing the shield can be the most challenging part of the build. You’re already a hero for building your own rig; you can catch a break without feeling guilty.

我將從主板開始。首先讓我說，如果您要使用多個GPU，那么在不修改您的情況的情況下該構建將不適用。我決定用單個GPU構建mini-ITX外形(即小型)計算機，因為這是我的第一個構建，我認為這將具有足夠的挑戰性。另外，我希望我的房子(包括辦公室)具有裝飾性和整體感。我并不是想用一個霓虹發光的大塔來打造一個人類洞穴游戲天堂。但是我可以說，我喜歡這個板子！對于游戲玩家來說，這是我為系統購買的唯一RGB物品，它非常完美。但是從實用的角度來講，真正的好處是內置的I / O防護板。正如一位有幫助的youtube游戲計算機組裝人員指出的那樣，安裝防護罩可能是構建過程中最具挑戰性的部分。您已經是建造自己的鉆機的英雄。您可以休息而不會感到內catch。

案件 (Case)

Thermaltake Core V1 Snow Edition

I decided on the case early in the process, because it determined the sizes that would be possible for some of the other components. It’s also pretty fun, because there are a lot of options. I chose the Core V1 because, while it’s certainly a mini, it isn’t super small, so there’s still plenty of room for cables, etc. Some things to watch out for are: 1) the CPU cooler height, 2) the length of the GPU, and 3) the length of the power supply (PSU). This case is incredibly well designed. I like the fact that the board sits upright instead of sideways, so your components aren’t ‘hanging on for dear life’ as one reviewer pointed out.

我在此過程的早期就決定了該案例，因為它確定了其他某些組件可能的大小。這也很有趣，因為有很多選擇。我選擇Core V1的原因是，雖然它肯定是微型的，但它并不是超級小，因此仍然有足夠的空間容納電纜等。需要注意的一些事情是：1)CPU散熱器的高度，2)長度。 3)電源長度(PSU)。這種情況下設計得非常好。我喜歡董事會直立而不是側放的事實，因此您的組件不會像珍貴的生命那樣“垂死掙扎”。

中央處理器 (CPU)

Intel Core i7–8700K

英特爾酷睿i7–8700K

I think I may have over-bought on the processor. I had to have generation 8 to fit the motherboard, but the ‘K’ in the model number means that the processor is unlocked and so can be ‘overclocked.’ This is gamer language for pushing the processor to go faster than normal; however, my board doesn’t support this functionality anyhow (it’s a B instead of a Z series).

我想我可能在處理器上買了過多。我必須擁有第8代才能適合主板，但是型號中的“ K”表示處理器已解鎖，因此可以“超頻”。這是一種游戲語言，用于推動處理器比正常運行更快。但是，我的開發板不支持此功能(它是B系列而不是Z系列)。

CPU散熱器/散熱器 (CPU cooler / heatsink)

Noctua NH-U9S with NF-A9 92mm Fan

帶有NF-A9 92毫米風扇的Noctua NH-U9S

The cooler might be one place on a small machine where you pay a bit more, but this is the most highly rated item (reviewer stars) on my list. It’s still less expensive than many liquid coolers (although not as lovely). Plus, who wants to burn things up ’cause they were too cheap to spend an extra $30. You will learn to love this baby.

散熱器可能是小型機器上的一處地方，您要多付一點錢，但這是我列表中評分最高的項目(評論者評分)。它仍然比許多液體冷卻器便宜(盡管不那么可愛)。另外，誰想把東西燒掉，因為它們太便宜了，無法多花30美元。您將學會愛這個嬰兒。

內存 (RAM)

Corsair Vengeance LPX 32GB (2x16GB) DDR4 DRAM 2666MHz

海盜船LPX 32GB(2x16GB)DDR4 DRAM 2666MHz

Not much to comment on for RAM. I decided to max out what the board could do. These sticks sit pretty low so it’s not hard to attach the fan on the heat sink to clear them.

對于RAM沒什么可評論的。我決定最大限度地發揮董事會的作用。這些棍子的位置很低，因此將風扇安裝在散熱器上以清除它們并不難。

存儲 (Storage)

Samsung 860 EVO 1TB 2.5 Inch SATA III SSD

三星860 EVO 1TB 2.5英寸SATA III SSD

For now I have one SSD. There’s dedicated space in the case to add a second later if needed.

現在，我有一個SSD。機箱中有專用空間，需要時可以再添加一秒鐘。

到目前為止的構建 (The Build So Far)

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供電單元 (Power Supply Unit)

EVGA Supernova 650 G3, 80 Plus Gold 650W, Fully Modular

EVGA Supernova 650 G3、80 Plus金650W，完全模塊化

For the PSU I went with the recommended power as specified by the GPU (‘Fully Modular’ means that no cables are pre-attached, so you only use what you need). The PSU was the part I had the most concern about fitting into the case, but in it went.

對于PSU，我使用了GPU指定的推薦功率(“完全模塊化”意味著沒有預先連接電纜，因此只使用所需的功率)。 PSU是我最想適應該案子的部分，但事與愿違。

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顯卡 (GPU)

MSI GeForce RTX 2070

微星GeForce RTX 2070

And lastly, the most important part. I chose the RTX 2070 due its performance/cost profile. Another plus with a custom machine is that you can update your GPU relatively easily in the future if needed.

最后，最重要的部分。我選擇RTX 2070是因為它具有性能/成本方面的優勢。自定義計算機的另一個優點是，如果需要，您將來可以相對輕松地更新GPU。

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成品 (The Finished Product)

With a little planning and luck, it all fit beautifully! Now that you’re done with hardware, you’re ready to start installing the software to turn your box into a mean Deep Learning machine.

稍加計劃和運氣，一切都很完美！既然您已經完成了硬件的準備工作，就可以開始安裝軟件了，從而將您的機器變成一臺普通的深度學習機器。