computer organization - cpu-architecture

Could you explain to me in detail what a "Clock Cycle" is?

Clock cycle, is a duration of a single, complete transition of a device clock. Essentially, digital electronic is synchronous, i.e., there is a central source of timing commands synchronizing all elements of a processor to occur simultaneously.
It is similar to the officer leading a brigade of infantry, ordering them to shout "left" every time they put their left foot forward - this way, soldiers don't stumble into each other.
A computer has a device fulfilling a similar purpose - it synchronizes the different portions of a processor, for instance, memory access units, arithmetic units, etc. It has a direct impact on the speed of the computer - it synchronizes the execution of sequences of operations, that together result in the speed of execution of a software program.

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CPU clock cycle misunderstanding

I can't well understand about CPU clock such as 3.4Ghz. I know this is that 3.4 billions clock cycle per second.
So here if machine use single clock cycle instruction, then It can execute about 3.4 billions instructions per second.
But in pipeline, basically it needs more cycles per instruction, but each cycle length is shorter than single clock cycle.
But although pipeline has more throughput, anyway cpu can do 3.4 billions cycle per second. So, it can execute 3.4 billions/5 instructions(if one instruction needs 5 cycles), which means less than single cycle implementation(3.4 > 3.4/5). What am I missing?
Does CPU clock such as 3.4Ghz just means for based on pipeline cycle, not for based on single cycle implentation?
Pipelining
Pipelining doesn't involve cycles shorter than a single clock cycle. Here's how pipelining works:
We have a complicated task to do. We take that task and break it down into a number of stages, each of which is relatively simple to carry out. We study the amount of work in each stage to make sure each stage takes about the same amount of time as any other.
With a processor, we do roughly the same thing--but in this case, it's not "install these fourteen bolts", it's things like fetching and decoding instructions, reading operands, executing (often a couple of stages here), and writing back results.
Like the automotive production line, we provide each stage of the pipeline with a specialized set of tools for doing exactly (and only) what is needed at that stage. When we finish doing one stage of processing on a car/instruction, it moves along to the next stage, and this stage gets the next car/instruction to process.
In an ideal situation, the process works (roughly) like this:
It took Ford about 12 hours to build one N car (the predecessor to the model T). Thanks primarily to pipelining the production line, it took only about 2 and a half hours to build a Model T. More importantly, even though a model T took 2.5 hours start to finish, that time was broken down into no fewer than 84 discrete steps, so when everything ran smoothly the production line as a whole could produce another car (about) every two minutes.
That didn't always happen though. If one stage ran short of parts, the stages after it had to wait. If the pause lasted very long, it would back things up so the preceding stages had to wait too.
The same can happen in a processor pipeline. For example, when a branch happens, the processor may have to wait a while before the next instruction can be fetched. If an instruction needs an operand from memory, that can lead to a pause (a "pipeline bubble") as well.
To prevent pauses in his pipeline, Henry Ford hired people to study the stages, figure out how many of each kind of part would need to be on hand for each stage, and so on. I don't know for sure, but I think it's a fair guess that there were probably a few people designated to watch the supply of parts at different stations, and send somebody running to let a warehouse manager know if (for whatever reason) the supply of parts for a particular stage looked like it was running short so they'd need more soon.
Processors do a little of the same thing--they have things like branch predictors and prefetchers that attempt to figure out ahead of time what will be needed by the stream of instructions being executed, and trying to ensure that everything is on hand when its needed (with caches, for example, to temporarily store things that seem likely to be needed soon).
So, like the Model T, it takes some relatively long amount of time for each instruction to execute start to finish, but we get another product finished at much shorter intervals--ideally once a clock (but see my other answer--modern designs often execute more than one instruction per clock).
A typical modern CPU can execute a number of unrelated instructions (those that don't depend on the same resources) concurrently.
To do that, it typically ends up with a basic structure vaguely like this:
So, we have an instruction stream coming in on the left. We have three decoders, each of which can decode one instruction each clock cycle (but there may be limitations, so complex instructions all have to pass through one decoder, and the other two decoders can only do simple instructions).
From there, the instructions pass into a reorder buffer, which keeps a "scoreboard" of which resources are used by each instruction, and which resources are affected that instruction (where a "resource" would typically be something like a CPU register or a flag in the flags register).
The circuitry then compares those scoreboards to determine dependencies. For example, if one instruction writes to register 0, and a later one reads from register 0, then those instructions must execute serially. At each clock, it tries to find the N oldest instructions that don't have dependencies for execution.
There are then a number of independent execution units. Each of these is basically a "pure" function--it takes some inputs, carries out a specified transformation on it, and produces an output. This makes it easy to replicate them as needed, and have as many running in parallel as we want/can afford. Those are typically grouped, with one port going to each group. In each clock, we can send one instruction through that port to one of the execution units in that group. Once an instruction arrives at the execution unit, it may take more than one clock to finish execution.
Once those execute, we have a set of retirement units that take the results, and write them back to the registers in execution order. Again we have multiple units so we can retire multiple instructions per clock.
Note: this drawing tries to be semi-realistic about the rough number of decoders, retirement units, and ports that it depicts, but what it shows is a general idea--different CPUs will have more or fewer specific resources. For almost any of them, the number of decoded instructions in the scoreboard units is low though--a realistic number would be more like 50 instructions.
In any case, actual execution of instructions is one of the hardest parts of this to measure or reason about. The number of ports gives us a hard upper limit on the number of instructions that can start executing in any given clock. The number of decoders and retirement units give an upper limit on the number of instructions that can be started/finished per clock. The execution itself...well, there are a lot of execution units, and each one (at least potentially) takes a different number of clocks to execute an instruction.
With the design as shown above, you'd have a hard upper limit of three instructions per clock. That's the most you can decode or retire. With a different design, that could obviously go up or down (e.g., with 4 decoders, 4 ports and 4 retirement units, the upper limit could go up to 4).
Realistically, with that design you wouldn't normally expect to see three instructions execute in most clock cycles. There are enough dependencies between instructions that you'd probably expect closer to 2 as a long term average (and much more likely a little less than 2). Increasing the available resources (more decoders, more retirement units, etc.) will rarely help that a whole lot--you might get to an average of three instructions per clock, but hoping for four is probably unrealistic.
As others have noted the full details of how a modern CPU operates are complicated. But part of your question has a simple answer:
Does CPU clock such as 3.4Ghz just means for based on pipeline cycle,
not for based on single cycle implentation?
The clock frequency of a CPU refers to how many times per second the clock signal switches. The clock signal is not divided into smaller pipelined segments. The purpose of pipelining is to allow for faster clock switching speeds. So 3.4GHz refers to the number of times per second that a single pipeline stage can perform whatever work it needs to do when executing an instruction. The total work for executing an instruction is done over multiple cycles each of which could be in a different pipeline stage.
Your question also shows a some misconceptions about how pipelining works:
But although pipeline has more throughput, anyway cpu can do 3.4
billions cycle per second. So, it can execute 3.4 billions/5
instructions(if one instruction needs 5 cycles), which means less than
single cycle implementation(3.4 > 3.4/5). What am I missing?
In the simple case the throughput of a single cycle CPU and a pipelined CPU is the same. The latency of the pipelined CPU is higher because it requires more cycles (i.e. 5 in your example) to execute a single instruction. But after the pipeline is full the throughput could be the same as for a single cycle non-pipelined CPU. So in the simple case using your example a single-cycle CPU could execute 3.4 billion instructions in 1 seconds, while the pipelined CPU with 5 stages could execute 3.4 billion minus 5 instructions in 1 second. Subtracting 5 from 3.4 billion is a negligible difference, whereas dividing by 5 would be a very significant difference.
A couple of other things to note are that the simple case I described isn't really true because of dependencies between instructions that require pipeline stalls. And most modern CPUs can execute more than one instructions per cycle.

What is responsible for changing core's load and frequency in multicore processor

Having looked for a description of the multicore design i keep finding several diagrams, but all of them look somewhat like this:
I know from looking at i7z command output that different cores can run at different frequencies.
This would suggest that the decisions regarding which core will be given a new process and for changing the frequency of the core itself are done either by the operating system or by the control block of the core itself.
My question is: What controls the frequencies of each individual core? Is the job of associating a READY process with the specific core placed upon the operating system or is it done by something within the processor.
Scheduling processes/threads to cores is purely up to the OS. The hardware has no understanding of tasks waiting to run. Maintaining the OS's list of processes that are runnable vs. waiting for I/O is completely a software thing.
Migrating a thread from one core to another is done by kernel code on the original core storing the architectural state to memory, then OS code on the new core restoring that saved state and resuming user-space execution.
Traditionally, frequency and voltage scaling decisions are made by the OS. Take Linux as an example: The decision-making code is called a governor (and also this arch wiki link came up high on google). It looks at things like how often processes have used their entire time slice on the current core. If the governor decides the CPU should run at a different speed, it programs some control registers to implement the change. As I understand it, the hardware takes care of choosing the right voltage to support the requested frequency.
As I understand it, the OS running on each core makes decisions independently. On hardware that allows each core to run at different frequencies, the decision-making code doesn't need to coordinate with each other. If running a high frequency on one core requires a high voltage chip-wide, the hardware takes care of that. I think the modern implementation of DVFS (dynamic voltage and frequency scaling) is fairly high-level, with the OS just telling the hardware which of N choices it wants, and the onboard power microcontroller taking care of the details of programming oscillators / clock dividers and voltage regulators.
Intel's "Turbo" feature, which opportunistically boosts the frequency above the max sustainable frequency, does the decision making in hardware. Any time the OS requests the highest advertised frequency, the CPU uses turbo when power and cooling allow.
Intel's Skylake takes this a step further: The OS can hand full control over DVFS to the hardware, optionally with constraints. That lets it react from microsecond to microsecond, rather than on a timescale of milliseconds. This does actually allow better performance in bursty workloads, because more power budget is available for turbo when it's useful. A few benchmarks are bursty enough to observe this, like some browser / javascript ones IIRC.
There was a whole talk about Skylake's new power management at IDF2015, check out the slides and/or archived webcast. The old method is described in a lot of detail there, too, to illustrate the difference, so you should really check it out if you want more detail than my summary. (The list of other IDF talks is here, thanks to Agner Fog's blog for the link)
The core frequency is controlled by a given voltage applied to a core's "oscillator".
This voltage can be changed by the Operating System but it can also be changed by the BIOS itself if a high temperature is detected in the CPU.

For a Single Cycle CPU How Much Energy Required For Execution Of ADD Command

The question is obvious like specified in the title. I wonder this. Any expert can help?
OK, this is was going to be a long answer, so long that I may write an article about it instead. Strangely enough, I've been working on experiments that are closely related to your question -- determining performance per watt for a modern processor. As Paul and Sneftel indicated, it's not really possible with any real architecture today. You can probably compute this if you are looking at only the execution of that instruction given a certain silicon technology and a certain ALU design through calculating gate leakage and switching currents, voltages, etc. But that isn't a useful value because there is something always going on (from a HW perspective) in any processor newer than an 8086, and instructions haven't been executed in isolation since a pipeline first came into being.
Today, we have multi-function ALUs, out-of-order execution, multiple pipelines, hyperthreading, branch prediction, memory hierarchies, etc. What does this have to do with the execution of one ADD command? The energy used to execute one ADD command is different from the execution of multiple ADD commands. And if you wrap a program around it, then it gets really complicated.
SORT-OF-AN-ANSWER:
So let's look at what you can do.
Statistically measure running a given add over and over again. Remember that there are many different types of adds such as integer adds, floating-point, double precision, adds with carries, and even simultaneous adds (SIMD) to name a few. Limits: OSs and other apps are always there, though you may be able to run on bare metal if you know how; varies with different hardware, silicon technologies, architecture, etc; probably not useful because it is so far from reality that it means little; limits of measurement equipment (using interprocessor PMUs, from the wall meters, interposer socket, etc); memory hierarchy; and more
Statistically measuring an integer/floating-point/double -based workload kernel. This is beginning to have some meaning because it means something to the community. Limits: Still not real; still varies with architecture, silicon technology, hardware, etc; measuring equipment limits; etc
Statistically measuring a real application. Limits: same as above but it at least means something to the community; power states come into play during periods of idle; potentially cluster issues come into play.
When I say "Limits", that just means you need to well define the constraints of your answer / experiment, not that it isn't useful.
SUMMARY: it is possible to come up with a value for one add but it doesn't really mean anything anymore. A value that means anything is way more complicated but is useful and requires a lot of work to find.
By the way, I do think it is a good and important question -- in part because it is so deceptively simple.

Difference between Latency and Jitter in Operating-Systems

discussing criterias for Operating-Systems every time I hear Interupt-Latency and OS-Jitter. And now I ask myself, what is the Difference between these two.
In my opinion the Interrupt-Latency is the Delay from occurence of an Interupt until the Interupt-Service-Routine (ISR) is entered.
On the contrary Jitter is the time the moment of entering the ISR differs over time.
Is this the same you think?
Your understanding is basically correct.
Latency = Delay between an event happening in the real world and code responding to the event.
Jitter = Differences in Latencies between two or more events.
In the realm of clustered computing, especially when dealing with massive scale out solutions, there are cases where work distributed across many systems (and many many processor cores) needs to complete in fairly predictable time-frames. An operating system, and the software stack being leveraged, can introduce some variability in the run-times of these "chunks" of work. This variability is often referred to as "OS Jitter". link
Interrupt latency, as you said is the time between interrupt signal and entry into the interrupt handler.
Both the concepts are orthogonal to each other. However, practically, more interrupts generally implies more OS Jitter.

real-time in context of a game

I have a problem grokking the concept of real-time (IMO badly named, different meaning in different contexts). I understand real-time software as a software where time is a key variable. Events must occur at given time. Say, railway switch change at 15:02 and the next one must be at 15:05 no matter what.
But how about this example. In game, when player's FPS drops below 16 game exits and tell user to upgrade his hardware or kill other applications. So when one iteration of the game loop takes more than 1/16 of a second the output of the program is completely different.
Is it real-time(ish)? Can it be considered as a Real Time Computing?
Your question is hard to understand, are you referring to Real Time Computing, or simulating real time, or something completely different?
Simulating real time: It is possible to simulate real-time in a game by polling for events. Store the time of an event, and then when it comes time to render a frame, the game should repeatedly 'fast forward' by moving the current time to the time of the next event and handle the event. This should repeat until there are no more events, or the time is 'current'.
This requires you to have anything that is a function of time (such as velocity, position, acceleration) be calculated according to the current time. This means you would not have these attributes periodically updated, and allows your game to be deterministic, as the 'game time' is no longer dependent upon real time. It also makes things like game speed and pausing very simple to implement.
If you're referring to the concept of real-time systems, then I would say there's not enough information to determine whether that 'game loop' is 'real-time'. It depends on the operating environment of the game, and the logic in the 'game loop'. According to wikipedia, a real-time deadline must be met, regardless of system load.
In the rapidly approaching canonical article Fix your Timestep!, Glenn Fielder addresses numerous ways to handle this issue. While the article focuses primarily on physics, the key points are applicable to any system that represents a function of time, to wit, things dealing with moving things.
The executive summary of that article (which is well worth reading) is this:
You can make your physics deterministic (well, as much as can be achieved with imperfect input) by using discrete physics timesteps. It looks like this:
Render as fast as possible
Pass in a time delta that represents how long steps previous took this frame
Process delta time modulo timestep number of physics steps
Store the remainder of delta that you weren't able to process in an accumulator
That accumulator gets added to the next frame's time buffer. This requires some fine tuning such that temporary lag spikes due to e.g. a rapidly spinning player (which necessitates a lot of visibility determination over time) don't end up putting you in an inescapable time debt. If you wanted to intelligently guard against such an occurrence, you could have a sentry look for dangerous levels of accumulated time, which you could respond to by perhaps dropping a video frame.
Another advantage to using discrete timesteps is that they behave well in multiplayer games. If you have an authoritative server or node in a peer-to-peer configuration, the server can ensure that all clients' physics simulations are running at the same physics timeline. Discrete time blocks also simplifies things in rollback based multiplayer.
Edit:
Disclaimer: I've never written software for real-time myself, only worked in a company that had!
In response to really-real real-life Real Time software, it's unlikely that anyone has made a game that could be qualified as this, at least in software. (I'm not sure how one would qualify games on ROMs or games that don't run under a host OS?) While your example would be an attempt at real-time software, most real-time software goes through a period of certification in which the maximum amount of time spent per instruction or on a logical block of operation is determined. Games might come close to this in a sense when, for example, platform licensors have requirements (as I believe XBLA does) regarding minimum 30fps or similar. However, these certifications are usually established through a period of testing rather than through mathematical proof.