Sequoia: 20 Petaflops, 1.6 million cores, 1.6 Petabytes RAM

http://hpcinfo.wordpress.com/2009/02/05/sequoia-20-petaflops-16-million-cores-16-petabytes-ram-6-megawatts/

by timf • 17 years ago

25 28 17 years ago

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biohacker422• 17 years ago

It's interesting to think about the possible uses for a machine like that.

My own personal interest is protein folding.

Proteins are folding right now, as you read this, in every cell of your body, and they're doing it in linear time.

But computationally we're stuck with exponential time.

The day we find an algorithm for linear time protein folding, is the day the world changes at least as much as when penicillin was discovered.

anamax3• 17 years ago

> My own personal interest is protein folding.

> But computationally we're stuck with exponential time.

It's not that bad and it "recently" got a lot better.

Search for "shaw protein folding neutral territory".

bbgm2• 17 years ago

It's not even close. Shaw's work is good, but we are still not close to folding proteins from a linear sequence. The physics is just not there

fizx2• 17 years ago

Protein folding is NP-complete (Berger et al 1998). This implies that we can get fast heuristics for certain subclasses of proteins, but there is no general linear time protein folding solution.

biohacker422• 17 years ago

I don't know of anything in nature which solves the traveling sales person problem, but protein folding does progress in linear time in nature.

That may mean that proteins quickly collapse the probability space or have some other "trick" by which they are not NP-complete, or whatever, it is not magic.

There is a way and I'm hopeful we can find it.

bbgm2• 17 years ago

I do think that really understanding molecular machinery (known proteins and their dynamic interactions in atomistic glory) and true molecular recognition problems are what we should be doing.

That said, we need better physics to represent these interactions. The fields been relatively static when it comes to forcefields that really work.

lst6• 17 years ago

...and is it finally coming close to .00001 % of a human brain?

If someone is excited about that, what about the human brain itself? Just a simple information:

The human brain is the most complex thing in the whole universe, or: all of physical universe is less complex than a single human brain.

acro• 17 years ago

May I ask what is the basis of your estimate on the computational capacity of the human brain?

timf2• 17 years ago

Especially pointed question since the statement implies someone has crossed the chasm of the physical universe in order to measure this.

(since "all of physical universe is less complex than a single human brain" and the physical universe contains around 6.7 billion brains (that we know of))

lst6• 17 years ago

Intelligence can't be measured in huge numbers, and every single human brain is infinitely more intelligent than any possible computer.

It's not me saying this, but science.

kurtosis4• 17 years ago

So the human brain has about 10^11 neurons and about 10^4 synapses per neuron. Naively representing the state of each synapse with one byte requires 10^15 bytes that's about 500,000 PCs.

But neurons aren't necessarily the optimal substrate for "neural" computation. They have a cycle time of about 100 Hz. Electronics are potentially a factor of 10^8 faster. Neurons also have a lot of noise which surely reduces their information transmission capacity. Also there are major constraints on the neural tissue involving power consumption and stability against siezures. Also there are vast sections of the brain e.g. the cerebellum which are apparently devoted to problems like stabilizing posture and making smooth movements which can be solved much easier with electronic controls.

It's very plausible that we could achieve a factor of 100 or even 1000 over the brain. The bottleneck is human imagination; we don't have a clue how the thing works.

lst6• 17 years ago

That's not the point.

The human brain is quite "infinitely" interconnected, and this is something which not only would be really, really hard to solve with a physical machine: it's simply impossible.

I understand the fascination of a real super computer, but it's simply nothing compared to a single human brain...

lst6• 17 years ago

Let me explicitly repeat your statement:

You say that the human brain would (in theory) be able to create something more intelligent than itself?

(Are you aware of the irony?)

trominos• 17 years ago

Preface: I'm not particularly well schooled in either neuroscience or in the mechanics of microprocessors.

However, I'm very close to certain that your post is basically a lot of hand-waving that is ultimately not only poorly reasoned but also actually incorrect.

- - -

The question we're trying to answer is basically, "What's the computational capacity of the brain?"

But that's not really a good question to work with, because "computational capacity" isn't well-defined. [Actually, I'm not sure about that. I know that either it's not well-defined, or its definition is something that's clearly not what we want in this situation.]

So let's ask something that we can actually reason about, like, "Assuming infinite memory, roughly how many floating point operations per second would a computer need to be able to execute in order to direct a human body in a way that's indistinguishable from what a real person does -- in real time?"

And, okay, we really only want the brain's conscious thought and maybe some of its unconscious thought, but it's hard to make a well-defined question involving just those things, and I doubt that the answer to our question will be more than a few orders of magnitude off of what we're really after.

- - -

Anyway, your post does a really, really bad job of answering that question (or anything like it). Your worst offense: > "So the human brain has about 10^11 neurons and about 10^4 synapses per neuron. Naively representing the state of each synapse with one byte requires 10^15 bytes that's about 500,000 PCs."

Come on. Did the fact that you had to use the word "byte" not tip you off? YOU'RE DISCUSSING MEMORY. Nobody cares about memory, because the amount of memory needed to store the brain's state is vastly less than the number of operations needed to simulate its function in real time.

I seriously am not able to articulate how frustrated I am that at least 12 people felt justified in upvoting you without taking the time to process the first two sentences of your post.

Before I go, another treat: > "Electronics are potentially a factor of 10^8 faster."

No. Electronics are a factor of 10^8 "faster", when "faster" is taken to mean "more rapid in executing a cycle." Which is an absolutely pointless irrelevent piece of shit statistic.

What the fuck.

- - -

Anyway, let me wrap up this post by actually answering the above question as best we can, given the current state of scientific understanding (or, more precisely, my understanding of that state of understanding):

There are on the order of 10^10 neurons and on the order of 10^11 glial cells in the adult human brain. These cells are directed by untold numbers of chemoattractants. We have no good theoretical model for the behavior of these cells in huge numbers of situations.

Therefore, WE HAVE ABSOLUTELY NO FUCKING IDEA how much processing power it would take to simulate the brain's macro function. We can put an upper bound on it: we know that if we could simulate every atom in the brain to a reasonable degree of accuracy, we'd get human behavior. Obviously the number of FLOPS it would take to do such a thing is unreachable. And beyond that, I don't think it's fair to say we know anything at all.

Sequoia: 20 Petaflops, 1.6 million cores, 1.6 Petabytes RAM

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