No, literally: this field of computer science and engineering is called supercomputing,

不，從字面上看：計算機科學和工程的這一領域被稱為超級計算。

and several new machines may just smash all the records...with two nations neck and neck in a race to see who will get there first.

和幾臺新機器可能會打破所有的記錄......兩個國家並駕齊驅，看看誰會先到達那裡。

Supercomputers are pretty different from something like your laptop.

超級計算機與你的筆記本電腦這樣的東西是相當不同的。

They can take up whole BUILDINGS, and are used to solve some of the most complicated problems in the world.

它們可以佔據整個建築，並被用來解決世界上一些最複雜的問題。

Just by looking at them, they may not seem that different from a machine like the ENIAC,

僅僅通過觀察，它們可能看起來與ENIAC這樣的機器沒有什麼不同。

the first ever programmable digital computer.

第一臺可編程的數字計算機。

The ENIAC was capable of about 400 FLOPS.

ENIAC的能力約為400 FLOPS。

FLOPS stands for floating-point operations per second,

FLOPS代表每秒鐘的浮點運算。

which basically tells us how many calculations the computer can do per second.

這基本上告訴我們計算機每秒鐘能做多少次計算。

This makes measuring FLOPS a way of calculating computing power.

這使得測量FLOPS成為計算計算能力的一種方式。

So, the ENIAC was sitting at 400 FLOPS in 1945, and in the ten years it was operational,

是以，ENIAC在1945年就已經達到了400個FLOPS，在它運行的十年裡。

it may have performed more calculations than all of humanity had up until that point in time—

它所做的計算可能比全人類到那時為止所做的計算還要多。

that was the kind of leap digital computing gave us.

這就是數字計算給我們帶來的那種飛躍。

From that 400 FLOPS we upgraded to 10,000 FLOPS, and then a million, a billion, a trillion, a quadrillion FLOPS.

從那400個FLOPS，我們升級到10000個FLOPS，然後是一百萬、十億、一萬億、四萬億FLOPS。

That's petascale computing, and that's the level of today's most powerful supercomputers.

這就是petascale計算，這就是當今最強大的超級計算機的水準。

But what's coming next is exascale computing.

但接下來要做的是超大規模計算。

That's, let's see...18 zeroes.

那是，讓我們看看......18個零。

1 quintillion operations per second.

每秒1萬億次操作。

Exascale computers will be a thousand times better performing than the petascale machines we have now.

Exascale計算機的性能將比我們現在擁有的petascale機器好一千倍。

Or, to put it another way, if you wanted to do the same number of calculations that an exascale computer can do in ONE second...

或者，換個說法，如果你想在一秒鐘內做與超大規模計算機相同數量的計算......

you'd be doing math for over 31 billion years.

你會做超過310億年的數學運算。

So...what the heck do we need that kind of computing power for?

那麼......我們到底需要這種計算能力做什麼？

Large-scale phenomena like climate change have so many moving parts that are all affected by minute changes

像氣候變化這樣的大規模現象有如此多的活動部分，都會受到微小變化的影響

in all the other variables, and the effects of these changes need to be projected forward in time.

在所有其他變量中，這些變化的影響需要在時間上進行預測。

That's a really complex situation to simulate.

這是一個非常複雜的情況，要進行模擬。

On the other end of the spectrum, molecular interactions between cells and drug compounds are also extremely complex—

just on the nanoscale—and computer models of these interactions allow us to see the actual mechanisms

只是在納米尺度上，這些相互作用的計算機模型使我們能夠看到實際機制。

of how diseases make us sick and how different medicines could interrupt those interactions.

的疾病如何使我們生病，以及不同的藥物如何中斷這些相互作用。

Exascale computing will provide us with more power, speed, specificity, and accuracy than we've ever had before.

Exascale計算將為我們提供比以往更多的動力、速度、特殊性和準確性。

It'll be like looking at the world through a new pair of prescription glasses,

這將像通過一副新的處方眼鏡看世界一樣。

bringing into sharper focus everything from chemistry to genetics, aircraft design to nuclear physics, even energy grid planning.

使得從化學到遺傳學、飛機設計到核物理，甚至是能源網規劃等一切都變得更加突出。

But increased performance comes with increased cost.

但性能的提高伴隨著成本的增加。

Exascale systems have price tags in the hundreds of millions of dollars, and they require huge amounts of electricity to run.

Exascale系統的標價為數億美元，而且它們需要大量的電力來運行。

And just like with humans, running makes computers hot,

就像人類一樣，跑步會使計算機發熱。

so computing facilities consume even more energy (and cold water) to cool the computers down

是以，計算設施需要消耗更多的能源（和冷水）來為計算機降溫。

and keep them at optimum performance.

並使其保持最佳性能。

Computers that are unrivaled in their power are also unrivaled in their complexity.

在力量上無與倫比的計算機在複雜性上也是無與倫比的。

Exascale machines will, for lack of a better word, 'think' differently than their predecessors.

由於缺乏一個更好的詞，Exascale機器的 "思考 "方式將與它們的前輩不同。

So we're going to need to connect their processors in a different way.

所以我們需要以不同的方式來連接他們的處理器。

Not only that, but exascale processors have to connect to memory and storage in a different way too—

不僅如此，超大規模的處理器還必須以不同的方式連接到內存和存儲------。

and both of these will have to contain unprecedented amounts of information.

而這兩者都將必須包含前所未有的大量資訊。

From the software side, you essentially have to 'talk' to these computers in a different way than you do to petascale machines,

從軟件方面來看，你基本上必須以不同的方式與這些計算機 "對話"，而不是與石油級機器對話。

so if you want to take codes that were designed to run on petascale computers and now run them on an exascale machine...

是以，如果你想把設計用於在千萬億次計算機上運行的代碼，現在在超大規模機器上運行......

you gotta do some major code overhaul.

你必須做一些重大的代碼檢修。

Which all means...the dawn of exascale requires huge innovations in everything from the physical architecture of the hardware

這一切意味著......超大規模的到來需要從硬件的物理架構上進行巨大的創新。

to software programming to engineering the buildings these computers will live in.

從軟件編程到這些計算機將居住的建築工程。

So, when can we expect to see these mega machines?

那麼，我們什麼時候能看到這些巨型機器呢？

Well, the first exascale machine in the U.S. was slated to arrive at Argonne National Lab sometime in 2021,

好吧，美國的第一臺超大規模機器預計將在2021年的某個時候抵達阿貢國家實驗室。

but has been delayed.

但已被延後了。

That supercomputer is called Aurora, and its team plans to use Intel GPU computer chips—

那臺超級計算機被稱為Aurora，其團隊計劃使用英特爾GPU計算機芯片--

the slow development of which that seems to be holding things up.

緩慢的發展，這似乎阻礙了事情的發展。

So, the machine that was supposed to come online second has now moved into first place.

是以，本應第二個上線的機器現在已經升到了第一位。

That's the Frontier supercomputer, which may come online this year at Oak Ridge National Lab and will clock in at 1.5 exaflops.

這就是Frontier超級計算機，它可能於今年在橡樹嶺國家實驗室上線，速度將達到1.5 exaflops。

And in 2023 Frontier will be followed by El Capitan at Lawrence Livermore National Lab,

而在2023年，Frontier將被勞倫斯-利弗莫爾國家實驗室的El Capitan所取代。

a machine capable of 2 whole exaflops.

一臺能夠達到整整2個百億億次的機器。

That's a heck of a lot of power.

那是一個很大的力量。

But it remains to be seen if the U.S. will actually get to exascale computing first.

但是，美國是否真的會首先達到超大規模計算，還有待觀察。

Because China is also bringing three new exascale machines into the spotlight...

因為中國也正在將三臺新的超大規模機器帶到聚光燈下...

and may very well get there before anyone else.

而且很可能比其他人更早到達那裡。

Even though the U.S. and China are leading the pack,

儘管美國和中國正處於領先地位。

many other countries, from Japan to places in Europe, also have exascale machines in the works.

其他許多國家，從日本到歐洲的一些地方，也有正在進行的超大規模機器。

Again—the machine hardware itself is really just the skeleton of exascale computing.

同樣--機器硬件本身實際上只是超大規模計算的骨架。

To actually bring that maximum power to bear on some of the most complex problems scientists are trying to untangle today,

實際上，要把這種最大的力量用於解決科學家們今天試圖解決的一些最複雜的問題。

there's a whole lot more going on behind the scenes.

幕後還有很多事情要做。

So, software engineers—now's your time to shine.

是以，軟件工程師們--現在是你們大顯身手的時候了。

If you want more on boundary-breaking computing innovations, check out our video on 'hot' quantum computing chips here.

如果你想了解更多關於突破邊界的計算創新，請查看我們關於 "熱門 "量子計算芯片的視頻。

And if you have other computational news you want us to cover, let us know in the comments below.

如果你有其他希望我們報道的計算新聞，請在下面的評論中告訴我們。

Make sure you subscribe to Seeker for all your coverage of bits and bytes, and as always, thanks for watching.

請確保你訂閱Seeker，以獲得所有關於比特和字節的報道，並一如既往地感謝你的觀看。

I'll see ya in the next one.

下一次見。