or - how long ago would $173M have bought you the kind of power we carry around today in a pocket?
or - how long ago would $173M have bought you the kind of power we carry around today in a pocket?
Estimates put the processing power of an iPhone 5 at at around 2.7x times that of the Cray 2[2]
[1] http://www.theregister.co.uk/2012/03/08/supercomputing_vs_ho...
[2] http://pages.experts-exchange.com/processing-power-compared/
Mainframes in general too.
I'm currently listening to Soul of a New Machine.
Mainframes are great, already using almost[0] memory safe systems programming language on the 60's with Burroughs, followed by IBM and a few other vendors.
Virtualization and containers with the 360.
Bytecode as universal binary format with JIT/AOT at kernel level, DB based file system, System/38 and AS/400.
Object based OS, AS/400.
[0] - They still have the issue of leaks and double free though, but everything else is safe Algol style with explicit unsafe blocks/modules required.
I also find it kind of amusing that IBM, a primarily consulting company, developed AS/400, given that part of its sales pitch is that integrated database requires no maintenance and you can forget entirely about your IBM i and just leave it running for a decade.
It's a neat system. I wish I had the opportunity to use one. In many ways it feels like we're still catching up to what System/38 was doing in 1979.
That would be a great read.
My favorite Cray tidbit: for fun, Seymour Cray dug tunnels underneath his home, and had a lot of his breakthroughs while doing so.
he attributed the secret of his success to "visits by elves" while he worked in the tunnel:
"While I'm digging in the tunnel, the elves will often come to me with solutions to my problem."
https://en.wikipedia.org/wiki/Seymour_Cray#Personal_life"Seymour Cray was a man of few words. I was there for three weeks before I realized he was not the janitor."
So, if this was linear, we can all expect 130 petaflop computers around 2043 for around $3,500?
Lots of caveats here though, things aren't usually as linear as all this, and this is very much a back-of-a-napkin calculation.
Given that Moore's Law is creaking I wouldn't expect pocket petaflops any time soon. I'd expect a serious outbreak of cloudy clusters everywhere, and perhaps a dynamically reconfigurable Internet 2.0 with completely transparent non-localised computation.
This might change if computing finally goes optical and/or quantum. But if we're pushing electrons around wires, current hardware is close to the physical limits. The only way to speed it up is to build a lot more of it and speed up the connections.
I'll link the url when I've scanned my bookmarks.
psedit: look at jojomonkeyboy's comment http://www.techrepublic.com/blog/classics-rock/the-80s-super... he says an i7 2600 (not an i3) has less sustained compute power.
https://en.m.wikipedia.org/wiki/Cray_X-MP "The Cray-2, a completely new design, was introduced 1985. A very different compact four-processor design with from 64 MW (megaword) to 512 MW (512 MB to 4 GB) of main memory, it was specified to 500 MFLOPS but was slower than the X-MP on certain calculations due to its high memory latency.
The X-MP-succeeding Cray Y-MP series was announced in 1988; it also had a new design, replacing the 16-gate ECL gate arrays with a more compact VLSI gate array with larger circuit boards. It was a major improvement of the X-MP supporting up to eight processors."
Note latency is huge for these systems meaning for most workloads modern cellphones absolutely crush them.
I'm not sure how to do the calculation to find the minimum amount of power required for 130 petaflops, but it seems like it's well within the capacity of today's mobile batteries.
What we need to advance is specialized Deep Learning cores that are compact, fast and low power, so they don't kill the battery. On the other hand, for general apps it's much less necessary to make the CPU faster.
In a (simplified) nutshell: We can fit more transistors in a given unit of area because we make them smaller. That used to just mean we increased clock frequencies (make it faster) but comparatively recently (decade or two) meant we increased parallelism.
Moore's Law is expected to fail because we are now reaching the point where smaller transistors are very heavily impacted by actual limitations imposed by physics.
So while it is possible we'll have a technology shift and see similar performance gains, it won't really be Moore's Law anymore (unless we start using Pym Particles or something).
What kind of technology shift do you mean? Like a totally different computing paradigm?
But none seem all that promising and my gut is that we'll focus more on interconnects and algorithmic improvements.
But time will tell.
For those reading along, this is a fictional particle named after Hank Pym - AntMan - from Marvel comics. It's not a technology in a lab somewhere.
I don't have an estimate. My point was simply to explain to you why your logic was flawed as we are nearing the limits of what Moore's Law can give us without some pretty massive changes. This isn't a case of "Clock speeds are capped. We are doomed. Oh, wait, we can just put two slower ones on the same die" and is more "So... we are out of physical space..."
Trends are great when you are trying to make sense of data and estimate how to move forward. But they should not be used in a manner that ignores actual data.
I'd say a better estimate would be to assume density stops increasing around the point when feature size is the size of a silicon atom. I'm sure that'll be way off, but closer than estimating 21 more doublings.
I think it seem like there is a much larger anti-science sentiment then there is because these people have been given a fresh voice with social media and for the first time in a long time they can connect with each other and build echo chambers to shout at eachother in.
Some of this spilled out in the last election and provided a non-trivial number of votes for a candidate who was clearly a demogogue, instead of voting for a different demogogue who appealed less to the uneducated.
If you look at Apple's recent offerings, it would seem they think that time is more or less here.
I certainly almost never use the full computing power of anything I'm using – the limiting factors aren't hardware any more but the software running on it.
VR might just about squeeze through now, but given the hardware limitations - and the fact that people look really dorky using it - I'm not expecting it to drive a new explosion of user interest.
We really need some completely new tech to drive a new wave of innovation. The obvious candidates are optical/quantum and perhaps direct neural interfacing. Both are still science fiction, but that may change by 2030.
More extreme technologies may also be possible, but they're beyond speculative.
For now it may be useful to remember that technology rarely develops linearly, so speculating about future CPUs is like speculating about the future of transatlantic cruise liners, while ignoring the fact that someone somewhere is working on heavier than air flight.
I would really like to be excited by the prospect of neural interfacing, but all I can imagine is people catching computer viruses.