Measure the electricity consumed by a browser to render a webpage - energy

Is there a way to calculate the electricity consumed to load and render a webpage (frontend)? I was thinking of a 'test' made with phantomjs for example:
load a web page
scroll to the bottom
And measure how much electricity was needed. I can perhaps extrapolate from CPU cycle. But phantomjs is headless, rendering in real browser is certainly different. Perhaps it's impossible to do real measurements.. but with an index it may be possible to compare websites.
Do you have other suggestions?

It's pretty much impossible to measure this internally in modern processors (anything more recent than 286). By internally, I mean by counting cycles. This is because different parts of the processor consume different levels of energy per cycle depending upon the instruction.
That said, you can make your measurements. Stick a power meter between the wall and the processor. Here's a procedure:
Measure the baseline energy usage, i.e. nothing running except the OS and the browser, and the browser completely static (i.e. not doing anything). You need to make sure that everything is stead state (SS) meaning start your measurements only after several minutes of idle.
Measure the usage doing the operation you want. Again, you want to avoid any start up and stopping work, so make sure you start measuring at least 15 seconds after you start the operation. Stopping isn't an issue since the browser will execute any termination code after you finish your measurement.
Sounds simple, right? Unfortunately, because of the nature of your measurements, there are some gotchas.
Do you recall your physics classes (or EE classes) that talked about signal to noise ratios? Well, a scroll down uses very little energy, so the signal (scrolling) is well in the noise (normal background processes). This means you have to take a LOT of samples to get anything useful.
Your browser startup energy usage, or anything else that uses a decent amount of processing, is much easier to measure (better signal to noise ratio).
Also, make sure you understand the underlying electronics. For example, power is VA (voltage*amperage) where both V and A are in phase. I don't think this will be an issue since I'm pretty sure they are in phase for computers. Also, any decent power meter understands the difference.
I'm guessing you intend to do this for mobile devices. Your measurements will only be roughly the same from processor to processor. This is due to architectural differences from generation to generation, and from manufacturer to manufacturer.
Good luck.

Related

Why do we need to specify the number of flash wait cycles?

Especially when working with "faster" devices like STMF4xx/F7xx we need to specify the number of flash wait cycles, based on the supply voltage and the sys-clock frequency.
When the CPU fetches instructions/or constants this is done over the FLITF. Am I right with the assumption that the FLITF holds a CPU request as long as it can provide the requested data, making it impossible for other Bus-Masters to access flash meanwhile.
If this was true, why should it be important to any interface to know flash wait cycles. Like Cache does preload instructions so or so, independent if it knows how long to wait, no?
Because the flash interface isn't magic.
It has to meet the necessary setup and hold times for addressing and reading out the flash cells, which will vary somewhat depending on voltage. Taking the STM32F411 as an example (because I have that TRM handy), doing some maths with the voltage/frequency/wait-state table implies that a read from flash on one of those takes in the order of ~30ns above 2.7V, down to ~60ns below 2.1V.
Since the flash interface doesn't have its own asynchronous nanosecond-precision timekeeping ability (because that would be needlessly complicated, power-hungry, and silly), that translates to asserting its signals for n clock cycles, after which it can assume the data signals from the cells are stable enough to read back*. How does it know what the clock frequency is, and therefore what n should be? Simple: you, as the programmer who set the clock, tell it. Some hardware things are just infinitely easier to let software deal with.
* and then going through the further shenanigans of extracting the relevant 8, 16 or 32 bits out of the 128-bit line it's read, to finally spit that out the other side onto the AHB bus to the waiting CPU, obviously.

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.

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.

How to find the time value of operation to optimize new algorithm design?

My question is specific to iPhone, iPod, and iPad, since I am assuming that the architecture makes a big difference. I'm hoping there is either a specification somewhere (for the various chips perhaps), or a reliable way to measure T for each specific instruction. I know I can use any number of tools to measure aggregate processor time used, memory used, etc. I want to quantify at a lower level.
So, I'm able to figure out how many times I go through the main part of the algorithm. For example, I iterate n * (n-1) times in a naive implementation, and between n (best case) and n + n * (n-1) (worst case) in another. I can also make a reasonable count of the total number of instructions (+ - = % * /, and logic statements), and I can compare those counts, but that's assuming the weight of each operation is the same. Also, I don't have any idea how to weight the actual time value of a logic statement (if, else, for, while) vs a mathematical operator... is "if" as much work as "+" each time I use it? I would love to know where to find this information.
So, for clarity, my goal is to discover how much processor time I am demanding of the CPU (or GPU or any U) so that I can design an optimal algorithm around processor time. Can someone give me an idea of where to start for iOS hardware?
Edit: This link to ClockServices.c and SIMD stuff in the developer portal might be a good start for people interested in this. A few more cups of coffee tonight and I might get through it ;)
On a modern platform, processor time isn't the only limiting factor. Often, memory access is.
Still, processor time:
Your basic approach at an estimation for the processor load is OK, though, and is sensible: Make a rough estimate of the cost based on your knowledge of typical platforms.
In this article, Table 1 shows the times for typical primitive operations in .NET. While your platform may vary, the relative time is usually very similar. Maybe you can find - or even make - one for iStuff.
(I haven't come across one so thorough for other platforms, except processor / instruction set manuals, but they deal with assembly instructions)
memory locality:
A cache miss can cost you hundreds of cycles, a disk access a thousand times as much. So controlling your memory access patterns (i.e. reducing the working set, restructuring and accessing data in a cache-friendly way) is an important part of evaluating an algorithm.
xCode has instruments to measure performance of each function/operation, you can simply use them.