Understanding cpu frequency, thread selection and more - multithreading

With a 1270v3 and a single thread app I'm at the end of performance but when I watch monitoring tools like atop I don't understand how this whole stuff works. I tried to find a nice article about this sort of topic but they either have been explained in a language I don't understand or are not about the stuff I would like to know. I hope it is alright to ask this kind of stuff here.
From my understanding a single-thread app does only use one thread for all/most of the work. So the performance is defined by the single-thread power of the CPU.
A moment before I wrote this question I played around with CPU-frequency and noticed that although there are only two instances of the app running the usage is shared across all cores.
So I assume that the thread jumps around between these cores.
So I set the CPU scaling to performance with cpufreq-set -g performance. The result was that all CPU cores/threads stayed at about 2GHz like it was before besides one that is permanently on 3.5GHz (100%). As I only changed the scaling for one core, why is the usage still shared across all cores? I mean the app is running at about 300%, why doesn't it stick to the CPU core with the 100%?
Furthermore as I noticed that only one of the CPU's got scaled up I looked into the help page and found -r which should scale all cores with the performance settings. Unfortunately nothing does change. (Is this a bug in Ubuntu 1404?) So I used -c with the number 8 (8 threads) -> didn't work. 4 -> works but only scales 2 cores out of 8. 7 -> scaled 4 cores. So I'm wondering, does this not support hyper-threading or is the whole program that buggy?
However as I understand it, the CPU's with the max frequency together with the thread jump around in the monitoring tools as they display the average the usage, which than looks like shared. Did I figure this right?
Would forcing one cpu to 3.5GHz and forcing the app to this core improve performance or is all the stuff I'm wondering about only about avg calculation between the data they show each second.
If so am I right that I should run best with cpufreq-set -c 7 -g performance if power consumption doesn't matter?
Thanks for reading so far, I hope you have a moment to help me understand the whole thing.
Atop example screenshots:
http://i.imgur.com/VFEBvLx.png
http://i.imgur.com/cBKOnJM.png
http://i.imgur.com/bgQfwfU.png

I believe a lot of your confusion has to do with the fuzzy mapping of the capabilities of cpufreq to the actual capabilities of the hardware.
Here’s a description of what is taking place on the HW and in the OS.
A processor is a collection of cores on the same silicon substrate. The cores are what we used to call CPUs with some enhancements. CPUs now have the capability of running multiple HW threads (hyperthreading), each hardware thread being equivalent to one of the old type CPUs. Putting this all together, the 1270v3 is a quad core (if I recall correctly), meaning it has 4 cores on the same silicon substrate. Each core can support two HW threads, each HW thread being equivalent to what the OS calls a CPU (and I’ll call a virtual CPU). So from the OS perspective, the 1270v3 has 8 (virtual) CPUs.
The OS doesn’t see packages, cores or HW threads. It sees CPUs, and to it there appear to be 8 of them.
To further complicate the issue, modern processors have various HW supporting power saving states called P-states, C-states and package C-states. Why do I mention these? It’s because they are intimately associated with the frequency of the processor. And cpufreq professes to provide the user with control over the processor’s frequency.
Now, I’m not familiar with cpufreq outside of reading the manpage and other material on the web. From my reading, it has a lot of idiosyncrasies, so I’ll talk about what it is doing from a broad perspective.
In a general sense, cpufreq has a lot of generic capability that may or may not be supported by the HW or the kernel. This is confusing because it looks like the functionality is there but then things don’t happen as you would expect. For example, cpufreq gives the impression that you can set each CPU’s frequency independently. In reality, on a hyperthreaded system, two “CPUs” are associated with each core and must have the same frequency.
A lot of the functionality that cpufreq is supposed to control is associated with the power efficiency characteristics of the processor, but again, its mapping to the processor’s actual hardware capabilities is incomplete and misleading. Though cpufreq seems to allow you to set max and min frequencies, the processor hardware doesn’t work this way. In modern Intel processors, such as the 1270v3, there are something called P-states. These P-states are frequency-voltage pairs that slow down a processor’s frequency (and drop its voltage) to reduce the processor’s power consumption at the cost of the application taking longer to run. These frequency-voltage pairings aren’t arbitrary though cpufreq gives the impression that they are.
What does this all mean? In addition to the thread migration issues that the commenter mentioned, cpufreq isn’t going to behave the way you expect because it appears to have capability that it actually doesn’t, and the capability that it does actually have maps only roughly to the actual capabilities of the HW and OS.
I embedded some further comments in your text.
With a 1270v3 and a single thread app I'm at the end of performance but when I watch monitoring tools like atop I don't understand how this whole stuff works. I tried to find a nice article about this sort of topic but they either have been explained in a language I don't understand or are not about the stuff I would like to know. I hope it is alright to ask this kind of stuff here.
From my understanding a single-thread app does only use one thread for all/most of the work. [Yes, but this doesn’t mean that the thread is locked to a specific virtual CPU or core.] So the performance is defined by the single-thread power of the CPU. [It’s not that simple. The OS migrates threads around, it has its own maintenance processes, etc] A moment before I wrote this question I played around with CPU-frequency and noticed that although there are only two instances of the app running the usage is shared across all cores. So I assume that the thread jumps around between these cores. So I set the CPU scaling to performance with cpufreq-set -g performance. The result was that all CPU cores/threads stayed at about 2GHz like it was before besides one that is permanently on 3.5GHz (100%). As I only changed the scaling for one core, why is the usage still shared across all cores? I mean the app is running at about 300%, why doesn't it stick to the CPU core with the 100%? [Since I can’t see what you are observing, I don’t really understand what you are asking.]
Furthermore as I noticed that only one of the CPU's got scaled up I looked into the help page and found -r which should scale all cores with the performance settings. Unfortunately nothing does change. (Is this a bug in Ubuntu 1404?) So I used -c with the number 8 (8 threads) -> didn't work. 4 -> works but only scales 2 cores out of 8. 7 -> scaled 4 cores. [I haven’t used cpufreq so can’t directly speak to its behavior, but the manpage implies that “-c ” refers to a specific virtual CPU and not the number of virtual CPUs.] So I'm wondering, does this not support hyper-threading or is the whole program that buggy? [Again, I’m not sure from your explanation what you are doing, but the n->n/2 behavior makes sense to me. You can change the frequency of a core but since each core has two hyperthreads/virtual CPUs, two of those virtual CPUs must scale together.]
However as I understand it, the CPU's with the max frequency together with the thread jump around in the monitoring tools as they display the average the usage, which than looks like shared. Did I figure this right? [Again, I’m not sure what you are observing. Both physically and in atop, the CPU designation should not change, meaning CPU001 will always refer to the same virtual CPU. The core with the max frequency shouldn’t physically jump around, though the user thread may. Something to note is that monitoring tools can be pretty heavy users of the CPU. This heavy usage can make figuring out your processor usage difficult if it causes threads to jump around to different virtual CPUs.]
Would forcing one cpu to 3.5GHz and forcing the app to this core improve performance or is all the stuff I'm wondering about only about avg calculation between the data they show each second. [I found a pretty good explanation of atop with a lot of helpful screen shots: http://www.unixmen.com/linux-basics-monitor-system-resources-processes-using-atop/] If so am I right that I should run best with cpufreq-set -c 7 -g performance if power consumption doesn't matter? [It all depends upon what other processes are running on your system. If your system is mostly idle except for your processes, then forcing a core to a certain frequency won’t make a difference. [I’m suspicious of what a “governor” does. The language appears to refer to power-efficiency/performance (“balanced”, “powersave”, “performance”, etc) but the details don’t match the capability of today’s hardware.]
Thanks for reading so far, I hope you have a moment to help me

Related

Where to find ipc (or cpi) value of Intel processors (say skylake) when diff no of physical and logical cores are used?

I am very new to this field and my question might be too stupid but please help me understand the fundamental here.
I want to know the instruction per cycle (ipc) or clock per instruction (cpi) of recent intel processors such as skylake or cascade lake. And I am also looking for these values when different no of physical cores are used and when hyper threading is used.
I thought spec cpu2017 benchmark results could help me here, but I could not find my ans there. They just compare the total execution time by time taken by some reference machine and gives the ratio. Am I missing something here?
I thought this is one of the very first performance parameters and should be calculated and published by some standard benchmark, but I could not find any. Am I missing something here?
Another related question which comes to my mind (and I think everybody might want to know) is what is the best it can provide using all the cores and threads (least cpi and max ipc)?
Please help me find ipc / cpi value of skylake (any Intel processor) when say maximum (28) cores are used and when hyperthreading is also enabled.
The IPC cost of hyperthreading (or SMT in general on non-Intel CPUs) totally depends on the workload.
If you're already bottlenecked on branch mispredicts, cache misses, or long dependency chains (low ILP), having 2 threads running on the same core leads to minimal interference.
(Partitioning the ROB reduces the ability to find ILP in either thread, though, so again it depends on the details.)
Competitive sharing of uop cache and L1d/L1i / L2 caches also might or might not be a problem, depending on cache footprint.
There is no general answer independent of workload
Some workloads get a major speedup from using HT to double the number of logical cores. Some high-ILP workloads actually do worse because of cache conflicts. (Workloads that can already come close to saturating the front-end at 4 uops per clock on Intel before Icelake, for example).
Agner Fog's microarch guide says a bit about this for some microarchitectures that support hyperthreading. https://agner.org/optimize/
IIRC, some AMD CPUs have higher front-end throughput with hyperthreading, but I think only Bulldozer-family.
Max throughput is not affected by HT, and each core is independent. e.g. 4 uops per clock for a Skylake core. Doubling the number of physical cores always doubles theoretical uops / clock. Obviously not all workloads parallelize efficiently, so running more threads might need more total instructions/uops, and/or create more memory stalls for communication.
Hyperthreading just helps you come closer to that more of the time by letting 2 threads fill each other's "bubbles" from stalls.

Moving threads across CPUs with clock_gettime(CLOCK_MONOTONIC)

I've heard people complain that the WinAPI functions QueryPerformanceFrequency() and QueryPerforamnceCounter() can behave erratically and unstably when the OS decides to move the calling thread to a new physical CPU.
Does anybody know if clock_gettime(CLOCK_MONOTONIC) suffers from similar issues? Or is it more guaranteed to be stable?
Also, are the worries about QPF/QPC on WinAPI just a thing of the past? Or are they still concerns even today?
OP:
I've heard people complain that the WinAPI functions QueryPerformanceFrequency() and QueryPerforamnceCounter() can behave erratically and unstably when the OS decides to move the calling thread to a new physical CPU.
I'm not sure what you mean by "erratic" or "unstable." If you mean drift, or variance between cores, these concerns are probably based on computers that shipped 12-15 years ago (XP and Win2000-based OS). From Microsoft:
QPC is available on Windows XP and Windows 2000 and works well on most systems. However, some hardware systems' BIOS didn't indicate the hardware CPU characteristics correctly (a non-invariant TSC), and some multi-core or multi-processor systems used processors with TSCs that couldn't be synchronized across cores. Systems with flawed firmware that run these versions of Windows might not provide the same QPC reading on different cores if they used the TSC as the basis for QPC.
That has pretty much become a non-issue for most current hardware (see link, below).
OP:
Does anybody know if clock_gettime(CLOCK_MONOTONIC) suffers from similar issues? Or is it more guaranteed to be stable?
Well, any high-frequency clock has to come from somewhere. On a Windows box (since you asked about QPC), where is that value going to come from? Adding an additional layer to any call to QueryPerformanceCounter essentially guarantees less precision, as there will be more CPU instructions in the mix between "now" and "now as reported back to you by the OS" (and, although extremely unlikely, there would be a small increase in the possibility of preemption, contributing further loss of precision).
This applies equally to any Intel-based Linux/BSD/whatever boxes, as they have to run with the same hardware characteristics. In the Intel-architecture world, the highest frequency you'll be able to get is going to be a value based on RDTSC and the operating system's best effort to keep any TSC values as close as possible across cores or processors (at least in the absence of specialized hardware).
This is why any benchmarking should be an average performance expectation based on a large number of data points.
Microsoft actually has a pretty good document outlining the implementation characteristics of high-frequency timers, including HPET and ACPI power management times, and touches briefly on multi-clock and virtualization: http://msdn.microsoft.com/en-us/library/windows/desktop/dn553408(v=vs.85).aspx.
OP:
Also, are the worries about QPF/QPC on WinAPI just a thing of the past? Or are they still concerns even today?
For most of the world, yes. I work on server-based code where microseconds count (high frequency market data), but most people who think a few hundred microseconds are going to make or break their program are kidding themselves. Do you know how long it takes to serve a web page? The CPU itself gets bored with all that waiting, even with thousands of users.

Intel MSR frequency scaling per - thread

I'm extending the Linux kernel in order to control the frequency of some threads: when they are scheduled onto a core (any core!), the core's frequency is changed by writing the proper p-state to the register IA32_PERF_CTL, as suggested in Intel's manual.
But when different threads with different "custom" frequencies are scheduled, it appears that the throughput of all the thread increases, as if all the cores run at the maximum set frequency.
I did many trials and measurements in different conditions of load and configuration, but the result is the same.
After some trials with CPUFreq (with no running app, I set different frequencies on each core, and finally the measured frequencies, with cpufreq-info -w, were equal), I wonder if the CPU cores can really run at different, independent frequencies, or if there are hardware policies or constraints.
Finally, is there a CPU model which makes this fine-grained frequency scaling feasible?
The CPU I am using is Intel Core i5 750
You cannot control individual core frequencies for active cores. You can, however, control frequencies of all active cores to be the same. The reasons are in the previous answers - all cores are on the same active voltage plane.
Hopefully, the next-gen Haswell processors will make it possible to control each core separately.
I think you're missing a big piece of the picture!
Read up on power and clocks domains. All processor cores within a domain run at the same P-state (i.e., the same frequency and voltage). The P-state that all cores will run at in that domain will always be the P-state of the core requesting the highest P-state in that domain. The MSRs don't reflect this at all, nor do the interfaces that the kernel exposes.
Anandtech has a good article on this:
http://www.anandtech.com/show/2658/2
"This is all very similar to AMD's Phenom, but where the two differ is in how they handle power management. While AMD will allow individual cores to request different clock speeds, Nehalem attempts to run all of its cores at the same frequency; if one core is idle then it's simply power gated and the core is effectively turned off."
I haven't hooked a power-meter up to SB/IB, but my guess is that the behavior is the same.
cpufreq-info will display information about which cores need to be synchronous in their P-states:
[root#navi ~]# cpufreq-info
cpufrequtils 008: cpufreq-info (C) Dominik Brodowski 2004-2009
Report errors and bugs to cpufreq#vger.kernel.org, please.
analyzing CPU 0:
driver: acpi-cpufreq
CPUs which run at the same hardware frequency: 0 1 <---- THIS
CPUs which need to have their frequency coordinated by software: 0 <--- and THIS
maximum transition latency: 10.0 us.
At least because of that, I'd recommend going through cpufreq interfaces instead of directly setting registers, as well as making it possible to run on non-intel CPUs which might have uncommon requirements.
Also check on how to make kernel threads stick to specific core, to avoid unexpecteded switching, if you didn't do so already.
I want to thank everyone for the contribution!
Further investigating, I found other details I share with the community.
As suggested, Nehalem places all the cores in a single clock domain, so that the maximum frequency set among all the cores is applied to all of them; some tools may show different frequencies on idle cores, but it is sufficient to run any application to make the frequency raise to the maximum.
This, from my tests, also applies to Sandy Bridge, where cores and LLC slices all reside in the same frequency/voltage domain.
I assume that this behavior also happens with Ivy Bridge, as it is only a 'tick' iteration.
Instead, I believe that Haswell places cores and LLC slices in different, singular domains, thus enabling per-core frequencies. This is also advertized in several pages like
http://www.anandtech.com/show/8423/intel-xeon-e5-version-3-up-to-18-haswell-ep-cores-/4

Linux per-process resource limits - a deep Red Hat Mystery

I have my own multithreaded C program which scales in speed smoothly with the number of CPU cores.. I can run it with 1, 2, 3, etc threads and get linear speedup.. up to about 5.5x speed on a 6-core CPU on a Ubuntu Linux box.
I had an opportunity to run the program on a very high end Sunfire x4450 with 4 quad-core Xeon processors, running Red Hat Enterprise Linux. I was eagerly anticipating seeing how fast the 16 cores could run my program with 16 threads..
But it runs at the same speed as just TWO threads!
Much hair-pulling and debugging later, I see that my program really is creating all the threads, they really are running simultaneously, but the threads themselves are slower than they should be. 2 threads runs about 1.7x faster than 1, but 3, 4, 8, 10, 16 threads all run at just net 1.9x! I can see all the threads are running (not stalled or sleeping), they're just slow.
To check that the HARDWARE wasn't at fault, I ran SIXTEEN copies of my program independently, simultaneously. They all ran at full speed. There really are 16 cores and they really do run at full speed and there really is enough RAM (in fact this machine has 64GB, and I only use 1GB per process).
So, my question is if there's some OPERATING SYSTEM explanation, perhaps some per-process resource limit which automatically scales back thread scheduling to keep one process from hogging the machine.
Clues are:
My program does not access the disk or network. It's CPU limited. Its speed scales linearly on a
single CPU box in Ubuntu Linux with
a hexacore i7 for 1-6 threads. 6
threads is effectively 6x speedup.
My program never runs faster than
2x speedup on this 16 core Sunfire
Xeon box, for any number of threads
from 2-16.
Running 16 copies of
my program single threaded runs
perfectly, all 16 running at once at
full speed.
top shows 1600% of
CPUs allocated. /proc/cpuinfo shows
all 16 cores running at full 2.9GHz
speed (not low frequency idle speed
of 1.6GHz)
There's 48GB of RAM free, it is not swapping.
What's happening? Is there some process CPU limit policy? How could I measure it if so?
What else could explain this behavior?
Thanks for your ideas to solve this, the Great Xeon Slowdown Mystery of 2010!
My initial guess would be shared memory bottlenecks. From what you say, your performance pretty much flatlines after 2 CPUs. You initially blame Redhat, but I'd be curious to see what happens if you install Ubuntu on the same hardware. I assume, of course, that you're running 64 bit SMP kernels across both tests.
It's probably not possible that the motherboard would peak at utilizing 2 CPUs. You have another machine with multiple cores that has provided better performance. Do you have hyperthreading turned on with the new machine? (and how does that answer compare to the old machine?). You're not, by chance, running in a virtualized environment?
Overall, your evidence is pointing to a ludicrously slow bottleneck somewhere. As you said, you're not I/O bound, so that leaves the CPU and memory. Either something is wrong with the hardware, or something is wrong with the hardware. Test one by changing the other, and you'll narrow down your possibilities quickly.
Do some research on rlimit - it's quite possible the shell/user acct you're running in has some RH-default or admin-set resource limits in place.
When you see this kind of odd scaling behaviour, especially if problems are seen with multiple threads, but not multiple processes, one thing to start looking at is the impacts of lock contention and other synchronisation primitives, which can cause threads running on different processors to have to wait for each other, potentially forcing multiple cores to flush their cache to main memory.
This means memory architecture starts to come into play, and that's going to be substantially faster when you have 6 cores on a single piece of silicon than when you're coordinating across 4 separate processors. Specifically, the single CPU case likely isn't needing to hit main memory for locking operations at all - everything is likely being handled at the L3 cache level, allowing the CPU to get on with things while data is flushed to main memory in the background.
While I expect the OP has lost interest in the question after all this time (or may not even have access to the hardware any more), one way to check this would be to see if the scaling up to 4 threads improves if the process affinity is set to lock it to a single physical CPU. Even better though would be to profile the application itself to see where it is spending it's time.As you change architectures and increase the number of cores, it gets harder and harder to guess where the bottlenecks are, so you really need to start measuring things directly, as in this example: http://postgresql.1045698.n5.nabble.com/Sun-Donated-a-Sun-Fire-T2000-to-the-PostgreSQL-community-td2057445.html

Highly concurrent multi-threaded application requires hardware

I am looking for a hardware, which must run about 256 computationally intensive real-time concurrent tasks in 24 hour mode (one multi-threaded C application). Each task takes about 40-50 MFLOPs, so all tasks require about 10 GFLOPs. CPU-RAM speed is insignificant. All tasks must be managed by a Linux Kernel (32 bit, with SMP).
I am looking for a one-mainboard solution with one multi-core CPU (if such CPU exist). If such CPU doesn't exist, then I need one mulit-socket mainboard solution (with multiple CPUs).
Can you please recommend me any professional CPU/Mainboard solution which will satisfy such requirements? It is also very important that there are no issues with Linux Kernel (2.6.25). No virtualization, no needs in huge RAM or CPU cache. I also would prefer Intel architecture and well-proved stability. I still have doubts that it is feasible at all.
Thank you in advance.
UPDATE:
I think I have found a right answer here and here.
UltraSPARC T2 has 8 cores with 8 threads each. Integrated high-bandwidth memory and IO. The T5140 carries two of them for 128 hardware threads.
The theoretical max raw performance of the 8 floating point units is 11 Giga flops per second (GFlops/s). A huge advantage over other implementations however is that 64 threads can share the units and thus we can achieve an extremely high percentage of theoretical peak. Our experiments have achieved nearly 90% of the 11 Gflop/s. - (http://blogs.oracle.com/deniss/entry/floating_point_performance_on_the)
Rent some Amazon EC2 nodes.
Updated: How about PS3's then? The NASA uses them for their simulation engines.
Maybe use CPU+GPU's in commercial servers?
Build it around FPGAs: nowadays, some variants include processors that can run Linux.
Even though you've given us the specs you think you need, we might be able to help you out better if you tell us what the application is intended to accomplish, and how it was implemented.
There may be a better way to split the work up or deal with it rather than your current solution.
Not Intel architecture but these run linux and have 64 cores on a single die.
TILEPro64
Get a bunch of four- or eight-core machines and split the processing across the machines using some sort of grid or clustering software. Maybe have a look at Beowulf.
As you mentioned, 10GFlops isn't exactly to be sneezed at so in a single machine, it'll be expensive. There's also the problem what you do when the machine breaks, you're unlikely to have a second machine of similar spec available. If you build a cluster using commodity hardware, you're a little more resilient and it's easier to find replacement machines.
MFLOPS and GFLOPS are very poor indicators of how well a program can run on any given CPU. These days, cache footprint is much more important; perhaps branch prediction accuracy as well.
There's almost no way to gauge performance of a given application on different architectures without actually giving it a spin. And even then, you may not get a good idea if you were unlucky enough to unknowingly build with compiler options that ruined your cache footprint, or used a bad threading library, or any of a hundred other things.
I see you'd prefer intel, but if you need one chip, I will again suggest the cell processor -
its theoretical peak performance is arount 25GFlops - kernel 2.6.25 had support for it already.
You could try a pre-slim playstation 3 for experimenting with (that would cost you little) or get yourself a server-based solution at around US$8K - you will have to re-write and fine tune your threads to take advabtage of the SPU co-processors there, but you could achieve your computational needs without breaking a sweat with a single CELL (1 PPC core + 8 SPU's)
NB.: with a playstation 3, you'd have only 6 available co-processors - but you don't seen to be on a budget with this project -
So you could at least try IBM's cell developer kit, which offers an emulator, to see if you can code your solution to run on it.
Thre are commercially available CELL products, both as stand-alone servers in blade form factory, and PCI Express add-on boards for PC workstations from
Mercury Computer Systems:
http://www.mc.com/microsites/cell/products.aspx?id=6986
Mercury does not list any prices on the site, but the pricing seens to be around the previoulsy mentioned U$8000.00 for these PCI Express cards.
A playstation 3 videogame can be purchased for about U$300.00 - and would allow you to prototype your application, and check if it is up to the needed performance. (I myself got one and have Fedora 9 running on it, although I did that as a hobbyst and have not, so far, used it for any calculations - I had also put together a Playstation-3 12 machinne cluster for Molecular simulations at the local University. The application they run did not take advantage of the multimedia SPU's, while I was in touch with then. But even so, clocked at 3.5GHz they performed better than standard ,s imlarly priced, PC's, even considering PS3's are priced 5x higher around here)

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