Faster cpu wastes more time as compared to slower cpu - performance

Suppose I have a program that has an instruction to add two numbers and that operation takes 10 nanoseconds(constant, as enforced by the gate manufactures).
Now I have 3 different processors A, B and C(where A< B < C in terms of clock cycles). A's one clock cycle has 15 nanosec, B has 10 nanosec and C has 7 nanosec.
Firstly am I correct on my following assumptions-
1. Add operation takes 1 complete cycle of processor A(slow processor) and wastes rest of 5 ns of the cycle.
2. Add operation takes 1 complete cycle of processor B wasting no time.
3. Add operation takes 2 complete cycles(20 ns) of processor C(fast processor) wasting rest of the 20-14=7 ns.
If the above assumptions are correct then isn't this a contradiction to the regular assumption that processors with high clock cycles are faster. Here processor C which is the fastest actually takes 2 cycles and wastes 7ns whereas, the slower processor A takes just 1 cycle.

Processor C is fastest, no matter what. It takes 7 ns per cycle and therefore performs more cycles than A and B. It's not C's fault that the circuit is not fast enough. If you would implement the addition circuit in a way that it gives result in 1 ns, all processors will give the answer in 1 clock cycle (i.e. C will give you the answer in 7ns, B in 10ns and A in 15ns).
Firstly am I correct on my following assumptions-
1. Add operation takes 1 complete cycle of processor A(slow processor) and wastes rest of 5 ns of the cycle.
2. Add operation takes 1 complete cycle of processor B wasting no time.
3. Add operation takes 2 complete cycles(20 ns) of processor C(fast processor) wasting rest of the 20-7=13 ns.
No. It is because you are using incomplete data to express the time for an operation. Measure the time taken to finish an operation on a particular processor in clock cycles instead of nanoseconds as you are doing here. When you say ADD op takes 10 ns and you do not mention the processor on which you measured the time for the ADD op, the time measurement in ns is meaningless.
So when you say that ADD op takes 2 clock cycles on all three processors, then you have standardized the measurement. A standardized measurement can then be translated as:
Time taken by A for addition = 2 clock cycles * 15 ns per cycle = 30 ns
Time taken by B for addition = 2 clock cycles * 10 ns per cycle = 20 ns
Time taken by C for addition = 2 clock cycles * 07 ns per cycle = 14 ns
In case you haven't noticed, when you say:
A's one clock cycle has 15 nanosec, B has 10 nanosec and C has 7 nanosec.
which of the three processors is fastest?
Answer: C is fastest. It's one cycle is finished in 7ns. It implies that it finishes 109/7 (~= 1.4 * 108) cycles in one second, compared to B which finishes 109/10 (= 108) cycles in one second, compared to A which finishes only 109/15 (~= 0.6 * 108) cycles in one second.
What does a ADD instruction mean, does it purely mean only and only ADD(with operands available at the registers) or does it mean getting
the operands, decoding the instruction and then actually adding the
numbers.
Getting the operands is done by MOV op. If you are trying to compare how fast ADD op is being done, it should be compared by time to perform ADD op only. If you, on the other hand want to find out how fast addition of two numbers is being done, then it will involve more operations than simple ADD. However, if it's helpful, the list of all Original 8086/8088 instructions is available on Wikipedia too.
Based on the above context to what add actually means, how many cycles does add take, one or more than one.
It will depend on the processor because each processor may have the adder differently implemented. There are many ways to generate addition of two numbers. Quoting Wikipedia again - A full adder can be implemented in many different ways such as with a custom transistor-level circuit or composed of other gates.
Also, there may be pipelining in the instructions which can result in parallelizing of the addition of the numbers resulting in huge time savings.
Why is clock cycle a standard since it can vary with processor to processor. Shouldn't nanosec be the standard. Atleast its fixed.
Clock cycle along with the processor speed can be the standard if you want to tell the time taken by a processor to execute an instruction. Pick any two from:
Time to execute an instruction,
Processor Speed, and
Clock cycles needed for an instruction.
The third can be derived from it.
When you say the clock cycles taken by ADD is x and you know the processor speed is y MHz, you can calculate that the time to ADD is x / y. Also, you can mention the time to perform ADD as z ns and you know the processor speed is same y MHz as earlier, you can calculate the cycles needed to execute ADD as y * z.

I'm no expert BUT I'd say ...
the regular assumption that processors with high clock cycles are faster FOR THE VAST MAJORITY OF OPERATIONS
For example, a more intelligent processor might perform an "overhead task" that takes X ns. The "overhead task" might make it faster for repetitive operations but might actually cause it to take longer for a one-off operation such as adding 2 numbers.
Now, if the same processor performed that same operation 1 million times, it should be massively faster than the slower less intelligent processor.
Hope my thinking helps. Your feedback on my thoughts welcome.

Why would a faster processor take more cycles to do the same operation than a slower one?
Even more important: modern processors use Instruction pipelining, thus executing multiple operations in one clock cycle.
Also, I don't understand what you mean by 'wasting 5ns', the frequency determines the clock speed, thus the time it takes to execute 1 clock. Of course, cpu's can have to wait on I/O for example, but that holds for all cpu's.
Another important aspect of modern cpu's are the L1, L2 and L3 caches and the architecture of those caches in multicore systems. For example: if a register access takes 1 time unit, a L1 cache access will take around 2 while a normal memory access will take between 50 and 100 (and a harddisk access would take thousands..).

This is actually almost correct, except that on processor B taking 2 cycles means 14ns, so with 10ns being enough the next cycle starts 4ns after the result was already "stable" (though it is likely that you need some extra time if you chop it up, to latch the partial result). It's not that much of a contradiction, setting your frequency "too high" can require trade-offs like that. An other thing you might do it use more a different circuit or domino logic to get the actual latency of addition down to one cycle again. More likely, you wouldn't set addition at 2 cycles to begin with. It doesn't work out so well in this case, at least not for addition. You could do it, and yes, basically you will have to "round up" the time a circuit takes to an integer number of cycles. You can also see this in bitwise operations, which take less time than addition but nevertheless take a whole cycle. On machine C you could probably still fit bitwise operations in a single cycle, for some workloads it might even be worth splitting addition like that.
FWIW, Netburst (Pentium 4) had staggered adders, which computed the lower half in one "half-cycle" and the upper half in the next (and the flags in the third half cycle, in some sense giving the whole addition a latency of 1.5). It's not completely out of this world, though Netburst was over all, fairly mad - it had to do a lot of weird things to get the frequency up that high. But those half-cycles aren't very half (it wasn't, AFAIK, logic that advanced on every flank, it just used a clock multiplier), you could also see them as the real cycles that are just very fast, with most of the rest of the logic (except that crazy ALU) running at half speed.

Your broad point that 'a CPU will occasionally waste clock cycles' is valid. But overall in the real world, part of what makes a good CPU a good CPU is how it alleviates this problem.
Modern CPUs consist of a number of different components, none of whose operations will end up taking a constant time in practice. For example, an ADD instruction might 'burst' at 1 instruction per clock cycle if the data is immediately available to it... which in turn means something like 'if the CPU subcomponents required to fetch that data were immediately available prior to the instruction'. So depending on if e.g. another subcomponent had to wait for a cache fetch, the ADD may in practice take 2 or 3 cycles, say. A good CPU will attempt to re-order the incoming stream of instructions to maximise the availability of subcomponents at the right time.
So you could well have the situation where a particular series of instructions is 'suboptimal' on one processor compared to another. And the overall performance of a processor is certainly not just about raw clock speed: it is as much about the clever logic that goes around taking a stream of incoming instructions and working out which parts of which instructions to fire off to which subcomponents of the chip when.
But... I would posit that any modern chip contains such logic. Both a 2GHz and a 3GHz processor will regularly "waste" clock cycles because (to put it simply) a "fast" instruction executed on one subcomponent of the CPU has to wait for the result of the output from another "slower" subcomponent. But overall, you will still expect the 3GHz processor to "execute real code faster".

First, if the 10ns time to perform the addition does not include the pipeline overhead (clock skew and latch delay), then Processor B cannot complete an addition (with these overheads) in one 10ns clock cycle, but Processor A can and Processor C can still probably do it in two cycles.
Second, if the addition itself is pipelined (or other functional units are available), then a subsequent non-dependent operation can begin executing in the next cycle. (If the addition was width-pipelined/staggered (as mentioned in harold's answer) then even dependent additions, logical operations and left shifts could be started after only one cycle. However, if the exercise is constraining addition timing, it presumably also prohibits other optimizations to simplify the exercise.) If dependent operations are not especially common, then the faster clock of Processor C will result in higher performance. (E.g., if a dependence stall occurred every fourth cycle, then, ignoring other effects, Processor C can complete four instructions every five 7ns cycles (35 ns; the first three instruction overlap in execution) compared to 40ns for Processor B (assuming the add timing included pipelining overhead).) (Note: Your assumption 3 is incorrect, two cycles for Processor C would be 14ns.)
Third, the extra time in a clock cycle can be used to support more complex operations (e.g., preshifting one operand by a small immediate value and even adding three numbers — a carry-save adder has relatively little delay), to steal work from other pipeline stages (potentially reducing the number of pipeline stages, which generally reduces branch misprediction penalties), or to reduce area or power by using simpler logic. In addition, the extra time might be used to support a larger (or more associative) cache with fixed latency in cycles, reducing miss rates. Such factors can compensate for the "waste" of 5ns in Processor A.
Even for scalar (single issue per cycle) pipelines clock speed is not the single determinant of performance. Design choices become even more complex when power, manufacturing cost (related to yield, adjusted according to sellable bins, and area), time-to-market (and its variability/predictability), workload diversity, and more advanced architectural and microarchitectural techniques are considered.
The incorrect assumption that clock frequency determines performance even has a name: the Megahertz myth.

Related

Is time cost of integer multiplication the same as any binary operation on ARM or Intel processors?

Is the processing time of an integer multiplication the same as any integer binary operation on modern CPU with pipelining (e.g Intel, ARM) ?
In the Assembly documentation of Intel, it is said that an integer multiplication takes 1 cycle, like any integer binary operation. Is this cycle equivalent to the time duration supposing the operations are pipelined ?
There are more than the cycles to consider:
latency
pipeline
While the results of ALU instructions are instantaneous, multiply instructions have to go through MAC(multiply accumulate) which usually costs more cycles and comes with a latency of multiple cycles.
And often there is only one MAC unit which means the core doesn't allow two mul instructions to be dual issued.
example: ARMv5E:
smulxy(16bit): one cycle plus three cycles latency
mul(32bit): two cycles plus three cycles latency
umull(64bit): three cycles plus four(lower half) and five(upper half) cycles latency
No, multiply is much more complicated than XOR, ADD, OR, NOT, etc. While binary makes it much easier than base 10 you still have to have a larger adder (than just a two operand ADD or other operation).
Take the bits abcd
abcd
* 1011
========
abcd
abcd.
0000..
+abcd...
=========
In base 10 like grade school you had to multiply each time, you are still multiplying here but only by one or zero so either you copy and shift the first operand or you copy and shift zeros. And it gets very big, addition is cascaded. Look up xor gate at wikipedia and see the full adder or just google it. You have a single column adder for a simple two operand add with three inputs and two outputs but the carry out of one bit is the carry in of the other. No logic is instantaneous even a single transistor inversion (NOT) takes a non-zero amount of time. You can start to think about how many gates are lined up just to make one 32 bit two operand ADD, and then think about a 32 bit multiply where each adder is 32 operand bits and some number of carry bits, and then all of that is cascaded. The chip real estate and the time to settle multiply almost exponentially for multiply, and you then start to worry about can you meet timing (can you settle the msbit of the result within the desired/designed clock speed).
So you will see optimizations made including multiple pipe stages, not 32 clocks to do a 32 bit multiply but maybe not one clock maybe two or four. With a dozen stage deep pipe though you can bury that in there and still meet an advertised one clock per instruction average.
Intel, ARM, etc the 1 cycle thing is an illusion, the math operation itself might take that long, but the execution of the instruction takes a few to a handful, and your pipe depths may be several to a dozen or more. There is limited use in attempting to count cycles these days. And feeding the pipe and handling memory operations tend to dominate the performance not the pipe/instructions themselves outside a carefully crafted sim of the core.
For the cortex-ms which are perhaps not what you are asking about but are very much part of our daily life you see in the documentation that it is the chip vendor that can choose the larger faster multiply or the slower smaller that helps with overall chip size and perhaps performance. (I do not examine the cortex-a docs that much as I do not use them as often) A compile time option when they compile the core, there are many compile time options (which is why for any arm core cortex-m or cortex-a) you cannot compare, say, two cortex-m4s from different vendors or chip families within a vendor as they could have been compiled differently and behave/perform differently (they still execute the enabled instructions in the same functional way of course).
So no you cannot assume the "execution time" or "cycle time" of ANY instruction, and in particular ones like multiply and divide and anything floating point cannot assumed to be single cycle. Yes like all the other instructions the one cycle advertised is based on the pipeline effects, no instruction takes one cycle start to finish, and based on pipe depth of the design the multiply and divide may take more than one clock but be hidden by the pipe to still average one clock per instruction.
Note that this question is "too broad", as there are many Intel and ARM implementations past and present. And chip implementation details are often not available or protected by NDA, all you have if anything are public documents that can hide the reality.

Calculating Cycles Per Instruction

From what I understand, to calculate CPI, it's the percentage of the type of instruction multiplied by the number of cycles right? Does the type of machine have any part of this calculation whatsoever?
I have a problem that asks me if a change should be recommended.
Machine 1: 40% R - 5 Cycles, 30% lw - 6 Cycles, 15% sw - 6 Cycles, 15% beq 3 - Cycles, on a 2.5 GHz machine
Machine 2: 40% R - 5 Cycles, 30% lw - 6 Cycles, 15% sw - 6 Cycles, 15% beq 4 - Cycles, on a 2.7 GHz machine
By my calculations, machine 1 has 5.15 CPI while machine 2 has 5.3 CPI. Is it okay to ignore the GHz of the machine and say that the change would not be a good idea or do I have to factor the machine in?
I think the point is to evaluate a design change that makes an instruction take more clocks, but allows you to raise the clock frequency. (i.e. leaning towards a speed-demon design like Pentium 4, instead of brainiac like Apple's A7/A8 ARM cores. http://www.lighterra.com/papers/modernmicroprocessors/)
So you need to calculate instructions per second to see which one will get more work done in the same amount of real time. i.e. (clock/sec) / (clocks/insn) = insn/sec, cancelling out the clocks from the units.
Your CPI calculation looks ok; I didn't check it, but yes a weighted average of the cycles according to the instruction mix.
These numbers are obviously super simplified; any CPU worth building at 2.5GHz would have some kind of branch prediction so the cost of a branch isn't just a 3 or 4 instruction bubble. And taking ~5 cycles per instruction on average is pathetic. (Most pipelined designs aim for at least 1 instruction per clock.)
Caches and superscalar CPUs also lead to complex interactions between instructions depending on whether they depend on earlier results or not.
But this is sort of like what you might do if considering increasing the L1d cache load-use latency by 1 cycle (for example), if that took it off the critical path and let you raise the clock frequency. Or vice versa, tightening up the latency or reducing the number of pipeline stages on something at the cost of reducing frequency.
Cycles per instruction a count of cycles. ghz doesnt matter as far as that average goes. But saying that we can see from your numbers that one instruction is more clocks but the processors are a different speed.
So while it takes more cycles to do the same job on the faster processor the speed of the processor DOES compensate for that so it seems clear this is a question about does the processor speed account for the extra clock?
5.15 cycles/instruction / 2.5 (giga) cycles/second, cycles cancels out you get
2.06 seconds/(giga) instruction or (nano) seconds/ instruction
5.30 / 2.7 = 1.96296 (nano) seconds / instruction
The faster one takes a slightly less amount of time so it will run the program faster.
Another way to see this to check the math.
For 100 clock cycles on the slower machine 15% of those are beq. So 15 of the 100 clocks, which is 5 beq instructions. The same 5 beq instructions take 20 clocks on the faster machine so 105 clocks total for the same instructions on the faster machine.
100 cycles at 2.5ghz vs 105 at 2.7ghz
we want the amount of time
hz is cycles / second we want seconds on the top
so we want
cycles / (cycles/second) to have cycles cancel out and have seconds on the top
1/2.5 = 0.400 (400 picoseconds)
1/2.7 = 0.370
0.400 * 100 = 40.00 units of time
0.370 * 105 = 38.85 units of time
So despite taking 5 more cycles the processor speed differences is fast enough to compensate.
2.7/2.5 = 1.08
105/100 = 1.05
so 2.5 * 1.05 = 2.625 so a processor 2.625ghz or faster would run that program faster.
Now what were the rules for changing computers, is less time defined as a reason to change computers? What is the definition of better? How much more power does the faster one consume it might take less time but the power consumption might not be linear so it may take more watts despite taking less time. I assume the question is not that detailed, meaning it is vague meaning it is a poorly written question on its own, so it goes to what the textbook or lecture defined as the threshold for change to the other processor.
Disclaimer, dont blame me if you miss this question on your homework/test.
Outside an academic exercise like this, the real world is full of pipelined processors (not all but most of the folks writing programs are writing programs for) and basically you cant put a number on clock cycles per instruction type in a way that you can do this calculation because of a laundry list of factors. Make sore you understand that, nice exercise, but that specific exercise is difficult and dangerous to attempt on real world processors. Dangerous in that as hard as you work you may be incorrectly measuring something and jumping to the wrong conclusions and as a result making bad recommendations. At the same time there is very much the reality that faster ghz does improve some percentage of the execution, but another percentage suffers, and is there a net gain or loss. Or a new processor design faster or slower may have features that perform better than an older processor, but not all feature will be better, there is a tradeoff and then we get into what "better" means.

What are the relative cycle times for the 6 basic arithmetic operations?

When I try to optimize my code, for a very long time I've just been using a rule of thumb that addition and subtraction are worth 1, multiplication and division are worth 3, squaring is worth 3 (I rarely use the more general pow function so I have no rule of thumb for it), and square roots are worth 10. (And I assume squaring a number is just a multiplication, so worth 3.)
Here's an example from a 2D orbital simulation. To calculate and apply acceleration from gravity, first I get distance from the ship to the center of earth, then calculate the acceleration.
D = sqrt( sqr(Ship.x - Earth.x) + sqr(Ship.y - Earth.y) ); // this is worth 19
A = G*Earth.mass/sqr(D); // this is worth 9, total is 28
However, notice that in calculating D, you take a square root, but when using it in the next calculation, you square it. Therefore you can just do this:
A = G*Earth.mass/( sqr(Ship.x - Earth.x) + sqr(Ship.y - Earth.y) ); // this is worth 15
So if my rule of thumb is true, I almost cut in half the cycle time.
However, I cannot even remember where I heard that rule before. I'd like to ask what is the actual cycle times for those basic arithmetic operations?
Assumptions:
everything is a 64-bit floating number in x64 architecture.
everything is already loaded into registers, so no worrying about hits and misses from caches or memory.
no interrupts to the CPU
no if/branching logic such as look ahead prediction
Edit: I suppose what I'm really trying to do is look inside the ALU and only count the cycle time of its logic for the 6 operations. If there is still variance within that, please explain what and why.
Note: I did not see any tags for machine code, so I chose the next closest thing, assembly. To be clear, I am talking about actual machine code operations in x64 architecture. Thus it doesn't matter whether those lines of code I wrote are in C#, C, Javascript, whatever. I'm sure each high-level language will have its own varying times so I don't wanna get into an argument over that. I think it's a shame that there's no machine code tag because when talking about performance and/or operation, you really need to get down into it.
At a minimum, one must understand that an operation has at least two interesting timings: the latency and the throughput.
Latency
The latency is how long any particular operation takes, from its inputs to its output. If you had a long series of operations where the output of one operation is fed into the input of the next, the latency would determine the total time. For example, an integer multiplication on most recent x86 hardware has a latency of 3 cycles: it takes 3 cycles to complete a single multiplication operation. Integer addition has a latency of 1 cycle: the result is available the cycle after the addition executes. Latencies are generally positive integers.
Throughput
The throughput is the number of independent operations that can be performed per unit time. Since CPUs are pipelined and superscalar, this is often more than the inverse of the latency. For example, on most recent x86 chips, 4 integer addition operations can execute per cycle, even though the latency is 1 cycle. Similarly, 1 integer multiplication can execute, on average per cycle, even though any particular multiplication takes 3 cycles to complete (meaning that you must have multiple independent multiplications in progress at once to achieve this).
Inverse Throughput
When discussing instruction performance, it is common to give throughput numbers as "inverse throughput", which is simply 1 / throughput. This makes it easy to directly compare with latency figures without doing a division in your head. For example, the inverse throughput of addition is 0.25 cycles, versus a latency of 1 cycle, so you can immediately see that you if you have sufficient independent additions, they use only something like 0.25 cycles each.
Below I'll use inverse throughput.
Variable Timings
Most simple instructions have fixed timings, at least in their reg-reg form. Some more complex mathematical operations, however, may have input-dependent timings. For example, addition, subtraction and multiplication usually have fixed timings in their integer and floating point forms, but on many platforms division has variable timings in integer, floating point or both. Agner's numbers often show a range to indicate this, but you shouldn't assume the operand space has been tested extensively, especially for floating point.
The Skylake numbers below, for example, show a small range, but it isn't clear if that's due to operand dependency (which would likely be larger) or something else.
Passing denormal inputs, or results that themselves are denormal may incur significant additional cost depending on the denormal mode. The numbers you'll see in the guides generally assume no denormals, but you might be able to find a discussion of denormal costs per operation elsewhere.
More Details
The above is necessary but often not sufficient information to fully qualify performance, since you have other factors to consider such as execution port contention, front-end bottlenecks, and so on. It's enough to start though and you are only asking for "rule of thumb" numbers if I understand it correctly.
Agner Fog
My recommended source for measured latency and inverse throughput numbers are Agner's Fogs guides. You want the files under 4. Instruction tables: Lists of instruction latencies, throughputs and micro-operation breakdowns for Intel, AMD and VIA CPUs, which lists fairly exhaustive timings on a huge variety of AMD and Intel CPUs. You can also get the numbers for some CPUs directly from Intel's guides, but I find them less complete and more difficult to use than Agner's.
Below I'll pull out the numbers for a couple of modern CPUs, for the basic operations you are interested in.
Intel Skylake
Lat Inv Tpt
add/sub (addsd, subsd) 4 0.5
multiply (mulsd) 4 0.5
divide (divsd) 13-14 4
sqrt (sqrtpd) 15-16 4-6
So a "rule of thumb" for latency would be add/sub/mul all cost 1, and division and sqrt are about 3 and 4, respectively. For throughput, the rule would be 1, 8, 8-12 respectively. Note also that the latency is much larger than the inverse throughput, especially for add, sub and mul: you'd need 8 parallel chains of operations if you wanted to hit the max throughput.
AMD Ryzen
Lat Inv Tpt
add/sub (addsd, subsd) 3 0.5
multiply (mulsd) 4 0.5
divide (divsd) 8-13 4-5
sqrt (sqrtpd) 14-15 4-8
The Ryzen numbers are broadly similar to recent Intel. Addition and subtraction are slightly lower latency, multiplication is the same. Latency-wise, the rule of thumb could still generally be summarized as 1/3/4 for add,sub,mul/div/sqrt, with some loss of precision.
Here, the latency range for divide is fairly large, so I expect it is data dependent.

Calculate CPU cycles and its handling bits per second

I've wondered about the amount of bits that a given CPU can handles and how should I manage to calculate this specific value.
I wanted to make sure that my thought and also my calculation are right.
Given that I have 64 bit CPU which feature 2.3 Ghz. The amount of bits that being handled per second should be the following :
(2.3 * 10^9) * 64
Is it that simple or I need consider any other variables?
Calculating throughput of a CPU is not as simple. Modern CPUs are pipelined and can execute multiple instructions concurrently if there are no data dependencies, yielding instructions per cycle (IPC) > 1. Some instructions may also have a higher latency than one cycle, meaning IPC can be < 1.
For some operations they might be constrained by memory bandwidth.
And then there are SIMD instructions which can process more data per instruction than the width of a single general purpose register.
http://www.agner.org/optimize/instruction_tables.pdf
https://en.wikipedia.org/wiki/Instruction_pipelining

Understanding CPU pipeline stages vs. Instruction throughput

I'm missing something fundamental re. CPU pipelines: at a basic level, why do instructions take differing numbers of clock cycles to complete and how come some instructions only take 1 cycle in a multi-stage CPU?
Besides the obvious of "different instructions require a different amount of work to complete", hear me out...
Consider an i7 with an approx 14 stage pipeline. That takes 14 clock cycles to complete a run-through. AFAIK, that should mean the entire pipeline has a latency of 14 clocks. Yet this isn't the case.
An XOR completes in 1 cycle and has a latency of 1 cycle, indicating it doesn't go through all 14 stages. BSR has a latency of 3 cycles, but a throughput of 1 per cycle. AAM has a latency of 20 cycles (more that the stage count) and a throughput of 8 (on an Ivy Bridge).
Some instructions cannot be issued every clock, yet take less than 14 clocks to complete.
I know about the multiple execution units. I don't understand how the length of instructions in terms of latency and throughput relate to the number of pipline stages.
I think what's missing from the existing answers is the existence of "bypass" or "forwarding" datapaths. For simplicity, let's stick with the MIPS 5-stage pipeline. Every instruction takes 5 cycles from birth to death -- fetch, decode, execute, memory, writeback. So that's how long it takes to process a single instruction.
What you want to know is how long it takes for one instruction to hand off its result to a dependent instruction. Say you have two consecutive ADD instructions, and there's a dependency through R1:
ADD R1, R2, R3
ADD R4, R1, R5
If there were no forwarding paths, we'd have to stall the second instruction for multiple cycles (2 or 3 depending on how writeback works), so that the first one could store its result into the register file before the second one reads that as input in the decode stage.
However, there are forwarding paths that allow valid results (but ones that are not yet written back) to be picked out of the pipeline. So let's say the first ADD gets all its inputs from the register file in decode. The second one will get R5 out of the register file, but it'll get R1 out of the pipeline register following the execute stage. In other words, we're routing the output of the ALU back into its input one cycle later.
Out-of-order processors make ubiquitous use of forwarding. They will have lots of different functional units that have lots of different latencies. For instance, ADD and AND will typically take one cycle (TO DO THE MATH, putting aside all of the pipeline stages before and after), MUL will take like 4, floating point operations will take lots of cycles, memory access has variable latency (due to cache misses), etc.
By using forwarding, we can limit the critical path of an instruction to just the latencies of the execution units, while everything else (fetch, decode, retirement), it out of the critical path. Instructions get decoded and dumped into instruction queues, awaiting their inputs to be produced by other executing instructions. When an instruction's dependency is satisfied, then it can begin executing.
Let's consider this example
MUL R1,R5,R6
ADD R2,R1,R3
AND R7,R2,R8
I'm going to make an attempt at drawing a timeline that shows the flow of these instructions through the pipeline.
MUL FDIXXXXWR
ADD FDIIIIXWR
AND FDIIIIXWR
Key:
F - Fetch
D - Decode
I - Instruction queue (IQ)
X - execute
W - writeback/forward/bypass
R - retire
So, as you see, the multiply instruction has a total lifetime of 9 cycles. But there is overlap in execution of the MUL and the ADD, because the processor is pipelined. When the ADD enters the IQ, it has to wait for its input (R1), and likewise so does the AND that is dependent on the ADD's result (R2). What we care about is not how long the MUL lives in total but how long any dependent instruction has to wait. That is its EFFECTIVE latency, which is 4 cycles. As you can see, once the ADD executes, the dependent AND can execute on the next cycle, again due to forwarding.
I'm missing something fundamental re. CPU pipelines: at a basic level, why do instructions take differing numbers of clock cycles to complete and how come some instructions only take 1 cycle in a multi-stage CPU?
Because what we're interested in is in speed between instructions, not the start to end time of a single instruction.
Besides the obvious of "different instructions require a different amount of work to complete", hear me out...
Well that's the key answer to why different instructions have different latencies.
Consider an i7 with an approx 14 stage pipeline. That takes 14 clock cycles to complete a run-through. AFAIK, that should mean the entire pipeline has a latency of 14 clocks. Yet this isn't the case.
That is correct, though that's not a particularly meaningful number. For example, why do we care how long it takes before the CPU is entirely done with an instruction? That has basically no effect.
An XOR completes in 1 cycle and has a latency of 1 cycle, indicating it doesn't go through all 14 stages. BSR has a latency of 3 cycles, but a throughput of 1 per cycle. AAM has a latency of 20 cycles (more that the stage count) and a throughput of 8 (on an Ivy Bridge).
This is just a bunch of misunderstandings. An XOR introduces one cycle of latency into a dependency chain. That is, if I do 12 instructions that each modify the previous instruction's value and then add an XOR as the 13th instruction, it will take one cycle more. That's what the latency means.
Some instructions cannot be issued every clock, yet take less than 14 clocks to complete.
Right. So?
I know about the multiple execution units. I don't understand how the length of instructions in terms of latency and throughput relate to the number of pipline stages.
They don't. Why should there be any connection? Say there's 14 extra stages at the beginning of the pipeline. Why would that effect latency or throughput at all? It would just mean everything happens 14 clock cycles later, but still at the same rate. (Though likely it would impact the cost of a mispredicted branch and other things.)

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