Panic in Multicore Land
MOBE2001 writes "There is widespread disagreement among experts on how best to design and program multicore processors, according to the EE Times. Some, like senior AMD fellow, Chuck Moore, believe that the industry should move to a new model based on a multiplicity of cores optimized for various tasks. Others disagree on the ground that heterogeneous processors would be too hard to program. The only emerging consensus seems to be that multicore computing is facing a major crisis. In a recent EE Times article titled 'Multicore puts screws to parallel-programming models', AMD's Chuck Moore is reported to have said that 'the industry is in a little bit of a panic about how to program multicore processors, especially heterogeneous ones.'"
I think "panic" is a bit of an over-reaction. I use a multicore CPU. I write software that runs on it. I'm not panicking.
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AMD's Chuck Moore presumably has a lot of self interest in pushing heterogeneous cores. They are combining ATI+AMD cores on a single die and selling the benefits in a range of environments including scientific computing etc.
So take it all with a grain of salt
--Q
Well, the most recent research into how the cortext works has some interesting leads on this. If we first assume that the human brain has a pretty interesting organization, then we should try to emulate it.
Recall that the human brain receives a series of pattern streams from each of the senses. These patterns streams are in turn processed in the most global sense--discovering outlines, for example--in the v1 area of the cortext, which receives a steady stream of patterns over time from the senses. Then, having established the broadest outlines of a pattern, the v1 cortext layer passes its assessment of what it saw the outline of to the next higher cortex layer, v2. Notice that v1 does not pass the raw pattern it receives up to v2. Rather, it passes its interpretation of that pattern to v2. Then, v2 makes a slightly more global assessment, saying that the outline it received from v1 is not only a face but a face of a man it recognizes. Then, that information is sent up to v4 and ultimate to the IT cortex layer.
The point here is important. One layer of the cortex is devoted to some range of discovery. Then, after it has assigned some rudimentary meaning to the image, it passes it up the cortex where a slightly finer assignment of meaning is applied.
The takeaway is this: each cortex does not just do more of the same thing. Instead, it does a refinement of the level below it. This type of hierarchical processing is how multicore processors should be built.
Can I have... errr... Two floating point, one generic math with extra cache and two RISC's.
If you mod this up, your slashdot background will turn into a beautiful sunset!
It is portable, scalable, standardized and supports many languages.
nemesis. Home of an experimental fe code.
That's why it's so important that languages begin to adopt threading primitives and immutable data structures. Java does a good job. Newer languages, like Clojure are built from the ground up with concurrency in mind.
This article is referring to AMD's Charles R. "Chuck" Moore, who worked on the POWER4 and PowerPC 601, not the language and chip designer Charles H. "Chuck" Moore who invented Forth, ColorForth, et al. and was interviewed on slashdot.
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...functional programming languages? Or flow programming?
What Mr Moore is saying does have a grain of truth, that generic will be beaten by specific in key functions. The Amiga proved that in 1985, being able to deliver a better graphical solution than workstations costing tens of thousands more. The key now is to figure out which specifics you can use without driving up the cost nor without compromizing the design ideal of a general purpose computer.
Karma Whoring for Fun and Profit.
I've been doing some scientific computing on the Cell lately, and heterogeneous cores don't make life very easy. At least with the Cell.
The Cell has one PowerPC core ("PPU"), which is a general purpose PowerPC processor. Nothing exotic at all about programming it. But then you have 6 (for the Playstation 3) or 8 (other computers) "SPE" cores that you can program. Transferring data to/from them is a pain, they have small working memories (256k each), and you can't use all C++ features on them (no C++ exceptions, thus can't use most of the STL). They also have poor speed for double-precision floats.
The SPEs are pretty fast, and they have a very fast interconnect bus, so as a programmer I'm constantly thinking about how to take better advantage of them. Perhaps this is something I'd face with any architecture, but the high potential combined with difficult constraints of SPE programming make this an especially distracting aspect of programming the Cell.
So if this is what heterogeneous-cores programming means, I'd probably prefer the homogeneous version. Even if they have a little less performance potential, it would be nice to have a 90%-shorter learning curve to target the architecture.
The idea of having to use Microsoft APIs to program future computers because the vendors only document how to get DirectX to work doesn't exactly thrill me. I think panic is perhaps too strong a word, but sheesh...
As I demonstrated in my thesis a parallel application can be shown to have certain critical and less critical parts. An optimal processing platform matches those requirements. The remainder of the platform will remain idle and burn away power for nothing. One should wonder what is better: a 2 GHz processor or 2x 1 GHz processors. My opinion is that, if it has no impact on performance, the latter is better.
There is an advantage to a symmetrical platform: you cannot misschedule your processes. It does not matter which processor takes a certain job. On a heterogeneous system you can make serious errors: scheduling your video process on your communications processor will not be efficient. Not only is the video slow, the communications process has to wait a long time (impacting comm. performance).
nosig today
When we wrote the OpenAMQ messaging software in 2005-6, we used a multithreading design that lets us pump around 100,000 500-byte messages per second through a server. This was for the AMQP project.
Today, we're making a new design - ØMQ, aka "Fastest. Messaging. Ever." - that is built from the ground up to take advantage of multiple cores. We don't need special programming languages, we use C++. The key is architecture, and especially an architecture that reduces the cost of inter-thread synchronization.
From one of the ØMQ whitepapers:
We don't get linear scaling on multiple cores, partly because the data is pumped out onto a single network interface, but we're able to saturate a 10Gb network. BTW ØMQ is GPLd so you can look at the code if you want to know how we do it.
My blog
Just build both and let the market decide.
rooooar
If you have 80 or more cores, I'd rather have 20 of them support specialty functions and be able to do them very fast (it would have to be a few (1-3) orders of magnitude faster than the general counterpart) and the rest do general processing. This of course needs the support of operating systems, but that isn't very hard to get. With 80 cores caching and threading models have to be rethought, especially caching - the operating system has to be more involved in caching than it currently is, because otherwise cache coherency won't be able to be done.
.NET will be much more popular as it is possible for them to take care a lot of these issues, which isn't or only possible in a limited way for languages like C and friends with static source code inspection.
This also means that programs will need to be written not just by using threads, "which makes it okay for multi-core", but with cpu cache issues and locality in mind. I think VMs like JVM, Parrot and
It takes a man to suffer ignorance and smile
Be yourself no matter what they say
This trend with multiple cores on the CPU is only an intermediate phase,
because it over saturates the memory bus, which is easy to remedy by
putting the cores on the memory chips, of which there are a number
comparable to the number of cores.
In other words, the CPUs will disappear, and there will be lots of smaller
core/memory chips, connected in a network. And they will be cheaper as well,
because they do not need so high a yeld.
Kim0
I have a 4-core workstation and ALREADY I get crap usage rates out of it.
Flick the CPU monitor to aggregate usage rate mode, and I rarely clear 35% usage, and I've never seem it higher than about 55% (and even that for only a second or two once an hour). A normal PC, even fairly heavily loaded up with apps, just can't use the extra power.
And since cores aren't going to get much faster, there's no real chance of getting big wins there either.
Unless you have a specialized workload (heavy number crunching, kernel compilation, etc) there's going to simply be no point having more parallelism.
So as far as I can tell, for general loads it seems to be inevitable that if we want more straight line speed, we'll need to start making hardware more attuned for specific tasks.
So in my 16-core workstation of the future, if my Photoshop needs to apply some relatively intensive transform that has to be applied linearly, it can run off to the vector core, while I'm playing Supreme Commander on one generic core (the game) two GPU cores (the two screens) and three integer-heavy cores (for the 3 enemy AIs), and the generic System Reserved Core (for interrupts, and low-level IO stuff) hums away underneath with no pressure.
Hetrogeny also has economics on it's side.
There's very little point having specialized cores when you've only got two.
Once there's no longer scarcity in quantity, you can achieve higher productivity by specialization.
Really, any specialized core that you can keep the CPU usage rates running higher than the overall system usage rate, is a net win in productivity for the overall computer. And over time, anything that increases productivity wins.
Perhaps, panic is a little strong. At the same time, programing languages such as Occam, that are built from the ground up seem very provocative now. Perhaps Occam's syntax could modified to a Python-type syntax for a more popularity.
[Although, personally, I prefer Occam's syntax over that of C's.]
http://en.wikipedia.org/wiki/Occam_programming_language
I think that a tread aware programming language would be good in our multi-core world.
https://www.youtube.com/c/BrendaEM
I'm curious how having specialized multi-core processors is different from having a single-core processor with specialized subunits. Ie, a single core x86 chip has a section of it devoted to implementing MMC, SSE, etc. Isn't having many specialized cores just a sophisticated way of re-stating that you have a really big single-core processor, in some sense?
You see? You see? Your stupid minds! Stupid! Stupid!
See, the thing to do with all these cores is run a physics simulation. Physics can be easily distributed to multiple cores by the principle of locality. Then insert into your physics simulation a CPU -- something simple like a 68k perhaps. Once you have the CPU simulation going, adjust the laws of physics in your simulation (increase the speed of light to 100c, etc) so that you can overclock your simulated 68k to 100Ghz. Your single-threaded app will scream on that.
P.S.: I know why this is impossible, so please don't flame me.
I have seen the future, and it is inconvenient.
Ugg is smart.
Ugg can program a CPU.
Two Uggs can program two CPUs.
Two Uggs working on the same task program two CPUs.
Uggs' program has a race condition.
Ugg1 thinks, it's Ugg2's fault.
Ugg2 thinks, it's Ugg1's fault.
Ugg1 hits Ugg2 on the head with a rock.
Ugg2 hits Ugg1 on the head with an axe.
Ugg1 is half as smart as he was before working with Ugg2.
Ugg2 is half as smart as he was before working with Ugg1.
Both Uggs now write broken code.
Uggs' program is now slow, wrong half the time, and crashes on that race condition once in a while.
Ugg does not like parallel computing.
Ugg will bang two rocks together really fast.
Ugg will reach 4GHz.
Ugg will teach everyone how to reach 4GHz.
Contrary to the popular belief, there indeed is no God.
The height of optimism: posting proof in the form of a 70-odd page thesis on a Slashdot. ;-)
I don't think we'll be Slashdotting your server any time soon, CBravo
Antiquis temporibus, nati tibi similes in rupibus ventosissimis exponebantur ad necem.
I have read many times that some algorithms are difficult or impossible to multi-thread. I envisage the next logical step is a two socket motherboard, where one socket could be used for a 8+ core cpu running at low clock rate (e.g. 2-3Ghz) and another socket for a single core running at the greatest frequency achievable to the manufacturing process (e.g. x2 to x4 the clock speed of the multi-core) with whatever cache size compromises are required.
This help get around yield issues of getting all cores to work at a very high frequency and the related thermal issues . This could be a boon to general purpose computer that have a mix of hard to multi-thread and easy to multi-thread programs - assuming the OS could be intelligent on which cores the tasks are scheduled on. The cores could or could not have the same instruction sets, but having the same instruction sets would be the easy first step.
For servers the real problem is I/O. Disks are slow, network bandwidth is limited (if you solve that then memory bandwidth is limited ;) ).
;).
;).
For most typical workloads most servers don't have enough I/O to keep 80 cores busy.
If there's enough I/O there's no problem keeping all 80 cores busy.
Imagine a slashdotted webserver with a database backend. If you have enough bandwidth and disk I/O, you'll have enough concurrent connections that those 80 cores will be more than busy enough
If you still have spare cores and mem, you can run a few virtual machines.
As for desktops - you could just use Firefox without noscript, after a few days the machine will be using all 80 CPUs and memory just to show flash ads and other junk
Been there, done that, already. The 8087 and its 80x87 follow-on co-processors were exactly that. Specialized processors for specific tasks. Guess what? We managed to use them just fine a mere 27 years ago. DSP's have come along since and been used as well. Graphic card GPU's are specialized co-processors for graphic intensive functions, and we talk to them just fine. They're already on the chipsets, and soon to be on the processor dies. I don't think this is anything new, or anything that programming can't handle.
"It's the height of ridiculousness to say for those 9 lines you get hundreds of millions."
It has been quite obvious to several people in the usenet news:comp.arch newsgroup that the future should give us chips that contain multiple cores with different capabilites:
:-(
As long as all these cores share the same basic architecture (i.e. x86, Power, ARM), it would be possible to allow all general-purpose code to run on any core, while some tasks would be able to ask for a core with special capabilites, or the OS could simply detect (by trapping) that a given task was using a non-uniform resource like vector fp, mark it for the scheduler, and restart it on a core with the required resource.
An OS interrupt handler could run better on a short pipeline in-order core, a graphics driver could use something like Larrabee, while SPECfp (or anything else that needs maximum performance from a single thread would run best on an Out-of-Order core like the current Core 2.
The first requirement is that Intel/AMD must develop the capability to test & verify multiple different cores on the same chip, the second that Microsoft must improve their OS scheduler to the point where it actually understands NUMA principles not just for memory but also cpu cores. (I have no doubt at all that Linux and *BSD will have such a scheduler available well before the time your & I can buy a computer with such a cpu in it!)
So why do I believe that such cpus are inevitable?
Power efficiency!
A relatively simple in-order core like the one that Intel just announced as Atom delivers maybe an order of magnitude better performance/watt than a high-end Core 2 Duo. With 16 or 80 or 256 cores on a single chip, this will become really crucial.
Terje
PS As other posters have noted, keeping tomorrow's multi-core chips fed will require a lot of bandwith, this is neither free nor low-power.
"almost all programming can be viewed as an exercise in caching"
Back in 2000 I realized that 50 Million transistors of 4004 the first processor ever created, would out perform a P4 with the same transistor count done in the same fab running at the same clock rates. it would be over 10x faster I work out. But how to use such a device?
I had been working with a 100 PC cluster of P4 based systems to do H.264 HDTV compression in realtime. I spread the compression function across the cluster using each system to work on a small part of the problem and flow the data across the CPU's.
Based on this I wanted to build an array of processors on one chip, but I am not a silicon person, just software, driver and some basic electronics. So I looked at various FPGA cores, Arm, MIPS, etc. Then I went to a talk giving by Chuck Moore, author of the language FORTH. He had been building his own CPU's for many years using his own custom tools.
I worked with Chuck Moore for about a year in 2001/2002 on creating a massive multi core processor based on Chucks stack processor.
The Idea was instead of having 1,2 or 4 large processor to have 49 (7 * 7) small light but fast processors in one chip. This would be for tacking a different set of problems then your classic cpus'. It wouldn't be for running and OS or word processing, but for Multimedia, and cryptography, and other mathematic problems.
The idea was to flow data across the array of processors.
Each processor would run at 6Ghz, with 64K word of Ram each.
21 Bit wide words and bus (based off of F21 processor)
this allows for 4x 5bit instructions on a stack processor that only has 32 instructions.
Since it's a stack processor they run more efficiently. So in 16K transistors, 4000 gates,
the F21 at 500 Mhz performed about the same as a 500Mhz 486 with JPEG compress and decompress.
With the parallel core design instead of a common bus or network between the processors there would only be 4 connections into and out of each processor. These would be 4 registers that are shared with it's 4 neighboring processors that are laid out in a grid. So each chip would have a north, south, east and west register.
Data would be processed in whats called a systolic array, where each core would pick up some data, perform operations on it and pass it along to the next core.
The chips with a 7x7 grid of processors would expose the 28(4x7) bus lines off the edge processors, so that these could be tiled into a much larger grid of processors.
Each chip could perform around 117 Billion instructions per second at 1 Watt of power.
Unfortunately I was unable to raise money, partly because I couldn't' get any commitment from Chuck.
below is some links and other misc information on this project. Sorry it's not better organized.
This was my project.
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http://www.enumera.com/chip/
http://www.enumera.com/doc/Enumeradraft061003.htm
http://www.enumera.com/doc/analysis_of_Music_Copyright.html
http://www.enumera.com/doc/emtalk.ppt
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This was Jeff foxes independent web site, he work on the F21 with Chuck.
http://www.ultratechnology.com/ml0.htm
http://www.ultratechnology.com/f21.html#f21
http://www.ultratechnology.com/store.htm#stamp
http://www.ultratechnology.com/cowboys.html#cm
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http://www.colorforth.com/ 25x Multicomputer Chip
Chucks site. 25x has been pulled down, but it's accessible on archive.org.
http://web.archive.org/web/*/www.colorfo
I am always doing that which I can not do, in order that I may learn how to do it. - Pablo Picasso
The issue of the lack of progress in creating tools to simplify multithreaded programming has been a topic of discussion for well over a decade. Most programmers just don't make much use of multithreading. They take advantage of multithreading because their Web server and database support it and the Web server runs each request in a separate thread. Even then, some activity is complex and is usually not further parallelized. Operating systems programmers and some realtime programmers tend to be good a multithreading and parallel programming, but this is a small minority of programmers. Heck, look st Rails, one of the most popular Web frameworks - it isn't thread safe!
Look at most people's screens. Even if they have multiple programs running, they tend to have the one they are working on full screen. Studies have shown that people who multitask are less efficient than people who do one job at a time. Perhaps we are not educated to look at problems as solvable in a parallel fashion or perhaps there is some other human based problem. Maybe like many other skills, being able to think and program in a multithreaded fashion is a talent that only a small fraction of the population has.
This "panic" isn't going away and there is NO quick fix on the programming horizon. The hardware designers can stuff more cores in the box, but programmers won't keep up. what can consume the extra CPU power are things like speech recognition, hand writing and gesture recognition and rich media. Each of the can run in its 1-4 cores and help us serial humans interact with those powerful computers more easily.