Chapter II: Interfaces
Last updated
Last updated
This chapter covers the inner workings of Go's interfaces.
Specifically, we'll look at:
How functions & methods are called at run time.
How interfaces are built and what they're made of.
How, when and at what cost does dynamic dispatch work.
How the empty interface & other special cases differ from their peers.
How interface composition works.
How and at what cost do type assertions work.
As we dig deeper and deeper, we'll also poke at miscellaneous low-level concerns, such as some implementation details of modern CPUs as well as various optimizations techniques used by the Go compiler.
Table of Contents
This chapter assumes you're familiar with Go's assembler ().
If and when running into architecture-specific matters, always assume linux/amd64.
We will always work with compiler optimizations enabled.
Quoted text and/or comments always come from the official documentation (including Russ Cox "Function Calls" design document) and/or codebase, unless stated otherwise.
As pointed out by Russ Cox in his design document about function calls (listed at the end of this chapter), Go has..:
..4 different kinds of functions..:
top-level func
method with value receiver
method with pointer receiver
func literal
..and 5 different kinds of calls:
direct call of top-level func (
func TopLevel(x int) {})direct call of method with value receiver (
func (Value) M(int) {})direct call of method with pointer receiver (
func (*Pointer) M(int) {})indirect call of method on interface (
type Interface interface { M(int) })indirect call of func value (
var literal = func(x int) {})
Mixed together, these make up for 10 possible combinations of function and call types:
direct call of top-level func /
direct call of method with value receiver /
direct call of method with pointer receiver /
indirect call of method on interface / containing value with value method
indirect call of method on interface / containing pointer with value method
indirect call of method on interface / containing pointer with pointer method
indirect call of func value / set to top-level func
indirect call of func value / set to value method
indirect call of func value / set to pointer method
indirect call of func value / set to func literal
(A slash separates what is known at compile time from what is only found out at run time.)
We'll first take a few minutes to review the three kinds of direct calls, then we'll shift our focus towards interfaces and indirect method calls for the rest of this chapter. We won't cover function literals in this chapter, as doing so would first require us to become familiar with the mechanics of closures.. which we'll inevitably do, in due time.
Let's have a quick look at the code generated for each of those 4 calls.
Direct call of a top-level function
Looking at the assembly output for Add(10, 32):
We see that, as we already knew from chapter I, this translates into a direct jump to a global function symbol in the .text section, with the arguments and return values stored on the caller's stack-frame.
It's as straightforward as it gets.
Russ Cox wraps it up as such in his document:
Direct call of top-level func: A direct call of a top-level func passes all arguments on the stack, expecting results to occupy the successive stack positions.
Direct call of a method with pointer receiver
First things first, the receiver is initialized via adder := Adder{id: 6754}:
(The extra-space on our stack-frame was pre-allocated as part of the frame-pointer preamble, which we haven't shown here for conciseness.)
Then comes the actual method call to adder.AddPtr(10, 32):
Looking at the assembly output, we can clearly see that a call to a method (whether it has a value or pointer receiver) is almost identical to a function call, the only difference being that the receiver is passed as first argument.
In this case, we do so by loading the effective address (LEAQ) of "".adder+28(SP) at the top of the frame, so that argument #1 becomes &adder (if you're a bit confused regarding the semantics of LEA vs. MOV, you may want to have a look at the links at the end of this chapter for some pointers).
Note how the compiler encodes the type of the receiver and whether it's a value or pointer directly into the name of the symbol: "".(*Adder).AddPtr.
Direct call of method: In order to use the same generated code for both an indirect call of a func value and for a direct call, the code generated for a method (both value and pointer receivers) is chosen to have the same calling convention as a top-level function with the receiver as a leading argument.
Direct call of a method with value receiver
As we'd expect, using a value receiver yields very similar code as above.
Consider adder.AddVal(10, 32):
Looks like something a bit trickier is going on here, though: the generated assembly isn't even referencing "".adder+28(SP) anywhere, even though that is where our receiver currently resides.
So what's really going on here? Well, since the receiver is a value, and since the compiler is able to statically infer that value, it doesn't bother with copying the existing value from its current location (28(SP)): instead, it simply creates a new, identical Adder value directly on the stack, and merges this operation with the creation of the second argument to save one more instruction in the process.
Once again, notice how the symbol name of the method explicitly denotes that it expects a value receiver.
There's one final call that we haven't looked at yet: (&adder).AddVal(10, 32).
In that case, we're using a pointer variable to call a method that instead expects a value receiver. Somehow, Go automagically dereferences our pointer and manages to make the call. How so?
How the compiler handles this kind of situation depends on whether or not the receiver being pointed to has escaped to the heap or not.
Case A: The receiver is on the stack
If the receiver is still on the stack and its size is sufficiently small that it can be copied in a few instructions, as is the case here, the compiler simply copies its value over to the top of the stack then does a straightforward method call to "".Adder.AddVal (i.e. the one with a value receiver).
(&adder).AddVal(10, 32) thus looks like this in this situation:
Boring (although efficient). Let's move on to case B.
Case B: The receiver is on the heap
If the receiver has escaped to the heap then the compiler has to take a cleverer route: it generates a new method (with a pointer receiver, this time) that wraps "".Adder.AddVal, and replaces the original call to "".Adder.AddVal (the wrappee) with a call to "".(*Adder).AddVal (the wrapper).
The wrapper's sole mission, then, is to make sure that the receiver gets properly dereferenced before being passed to the wrappee, and that any arguments and return values involved are properly copied back and forth between the caller and the wrappee.
(NOTE: In assembly outputs, these wrapper methods are marked as <autogenerated>.)
Here's an annotated listing of the generated wrapper that should hopefully clear things up a bit:
Obviously, this kind of wrapper can induce quite a bit of overhead considering all the copying that needs to be done in order to pass the arguments back and forth; especially if the wrappee is just a few instructions. Fortunately, in practice, the compiler would have inlined the wrappee directly into the wrapper to amortize these costs (when feasible, at least).
Note the WRAPPER directive in the definition of the symbol, which indicates that this method shouldn't appear in backtraces (so as not to confuse the end-user), nor should it be able to recover from panics that might be thrown by the wrappee.
WRAPPER: This is a wrapper function and should not count as disabling recover.
That's all for function and method calls, we'll now focus on the main course: interfaces.
Before we can understand how they work, we first need to build a mental model of the datastructures that make up interfaces and how they're laid out in memory. To that end, we'll have a quick peek into the runtime package to see what an interface actually looks like from the standpoint of the Go implementation.
The iface structure
An interface is thus a very simple structure that maintains 2 pointers:
tab holds the address of an itab object, which embeds the datastructures that describe both the type of the interface as well as the type of the data it points to.
data is a raw (i.e. unsafe) pointer to the value held by the interface.
While extremely simple, this definition already gives us some valuable information: since interfaces can only hold pointers, any concrete value that we wrap into an interface will have to have its address taken. More often than not, this will result in a heap allocation as the compiler takes the conservative route and forces the receiver to escape. This holds true even for scalar types!
We can clearly see how each time we create a new Addifier interface and initialize it with our adder variable, a heap allocation of sizeof(Adder) actually takes place. Later in this chapter, we'll see how even simple scalar types can lead to heap allocations when used with interfaces.
Let's turn our attention towards the next datastructure: itab.
The itab structure
An itab is the heart & brain of an interface.
First, it embeds a _type, which is the internal representation of any Go type within the runtime.
A _type describes every facets of a type: its name, its characteristics (e.g. size, alignment...), and to some extent, even how it behaves (e.g. comparison, hashing...)!
In this instance, the _type field describes the type of the value held by the interface, i.e. the value that the data pointer points to.
Second, we find a pointer to an interfacetype, which is merely a wrapper around _type with some extra information that are specific to interfaces.
As you'd expect, the inter field describes the type of the interface itself.
Finally, the fun array holds the function pointers that make up the virtual/dispatch table of the interface.
Notice the comment that says // variable sized, meaning that the size with which this array is declared is irrelevant.
We'll see later in this chapter that the compiler is responsible for allocating the memory that backs this array, and does so independently of the size indicated here. Likewise, the runtime always accesses this array using raw pointers, thus bounds-checking does not apply here.
The _type structure
Thankfully, most of these fields are quite self-explanatory.
I.e., assuming t is a _type, calling resolveTypeOff(t, t.ptrToThis) returns a copy of t.
The interfacetype structure
As mentioned, an interfacetype is just a wrapper around a _type with some extra interface-specific metadata added on top.
In the current implementation, this metadata is mostly composed of a list of offsets that points to the respective names and types of the methods exposed by the interface ([]imethod).
Conclusion
Here's an overview of what an iface looks like when represented with all of its sub-types inlined; this hopefully should help connect all the dots:
This section glossed over the different data-types that make up an interface to help us to start building a mental model of the various cogs involved in the overall machinery, and how they all work with each other. In the next section, we'll learn how these datastructures actually get computed.
Now that we've had a quick look at all the datastructures involved, we'll focus on how they actually get allocated and initiliazed.
NOTE: For the remainder of this chapter, we will denote an interface I that holds a type T as <I,T>. E.g. Mather(Adder{id: 6754}) instantiates an iface<Mather, Adder>.
Let's zoom in on the instantiation of iface<Mather, Adder>:
This single line of Go code actually sets off quite a bit of machinery, as the assembly listing generated by the compiler can attest:
As you can see, we've splitted the output into three logical parts.
Part 1: Allocate the receiver
A constant decimal value of 6754, corresponding to the ID of our Adder, is stored at the beginning of the current stack-frame.
It's stored there so that the compiler will later be able to reference it by its address; we'll see why in part 3.
Part 2: Set up the itab
It looks like the compiler has already created the necessary itab for representing our iface<Mather, Adder> interface, and made it available to us via a global symbol: go.itab."".Adder,"".Mather.
We're in the process of building an iface<Mather, Adder> interface and, in order to do so, we're loading the effective address of this global go.itab."".Adder,"".Mather symbol at the top of the current stack-frame.
Once again, we'll see why in part 3.
Semantically, this gives us something along the lines of the following pseudo-code:
That's half of our interface right there!
Now, while we're at it, let's have a deeper look at that go.itab."".Adder,"".Mather symbol.
As usual, the -S flag of the compiler can tell us a lot:
Neat. Let's analyze this piece by piece.
The first piece declares the symbol and its attributes:
As usual, since we're looking directly at the intermediate object file generated by the compiler (i.e. the linker hasn't run yet), symbol names are still missing package names. Nothing new on that front.
Other than that, what we've got here is a 40-byte global object symbol that will be stored in the .rodata section of our binary.
The second piece is a hexdump of the 40 bytes of data associated with the symbol. I.e., it's a serialized representation of an itab structure:
As you can see, most of this data is just a bunch of zeros at this point. The linker will take care of filling them up, as we'll see in a minute.
Notice how, among all these zeros, 4 bytes actually have been set though, at offset 0x10+4.
If we take a look back at the declaration of the itab structure and annotate the respective offsets of its fields:
We see that offset 0x10+4 matches the hash uint32 field: i.e., the hash value that corresponds to our main.Adder type is already right there in our object file.
The third and final piece lists a bunch of relocation directives for the linker:
rel 0+8 t=1 type."".Mather+0 tells the linker to fill up the first 8 bytes (0+8) of the contents with the address of the global object symbol type."".Mather.
rel 8+8 t=1 type."".Adder+0 then fills the next 8 bytes with the address of type."".Adder, and so on and so forth.
Once the linker has done its job and followed all of these directives, our 40-byte serialized itab will be complete.
Overall, we're now looking at something akin to the following pseudo-code:
We've got ourselves a ready-to-use itab, now if we just had some data to along with it, that'd make for a nice, complete interface.
Part 3: Set up the data
Remember from part 1 that the top of the stack (SP) currently holds the address of go.itab."".Adder,"".Mather (argument #1).
Also remember from part 2 that we had stored a $6754 decimal constant in ""..autotmp_1+36(SP): we now load the effective address of this constant just below the top of the stack-frame, at 8(SP) (argument #2).
So runtime.convT2I32 does 4 things: 1. It creates a new iface structure i (to be pedantic, its caller creates it.. same difference). 2. It assigns the itab pointer we just gave it to i.tab. 3. It allocates a new object of type i.tab._type on the heap, then copy the value pointed to by the second argument elem into that new object. 4. It returns the final interface.
Conceptually, we've now accomplished the following (pseudo-code):
To summarize all that just went down, here's a complete, annotated version of the assembly code for all 3 parts:
Keep in mind that all of this started with just one single line: m := Mather(Adder{id: 6754}).
We finally got ourselves a complete, working interface.
itab from an executableIn the previous section, we dumped the contents of go.itab."".Adder,"".Mather directly from the object files generated by the compiler and ended up looking at what was mostly a blob of zeros (except for the hash value):
To get a better picture of how the data is laid out into the final executable produced by the linker, we'll walk through the generated ELF file and manually reconstruct the bytes that make up the itab of our iface<Mather, Adder>.
Hopefully, this'll enable us to observe what our itab looks like once the linker has done its job.
First things first, let's build the iface binary: GOOS=linux GOARCH=amd64 go build -o iface.bin iface.go.
Step 1: Find .rodata
Let's print the section headers in search of .rodata, readelf can help with that:
What we really need here is the (decimal) offset of the section, so let's apply some pipe-foo:
Which means that fseek-ing 315392 bytes into our binary should place us right at the start of the .rodata section.
Now what we need to do is map this file location to a virtual-memory address.
Step 2: Find the virtual-memory address (VMA) of .rodata
The VMA is the virtual address at which the section will be mapped once the binary has been loaded in memory by the OS. I.e., this is the address that we'll use to reference a symbol at runtime.
The reason we care about the VMA in this case is that we cannot directly ask readelf or objdump for the offset of a specific symbol (AFAIK). What we can do, on the other hand, is ask for the VMA of a specific symbol.
Coupled with some simple maths, we should be able to build a mapping between VMAs and offsets and finally find the offsets of the symbols that we're looking for.
Finding the VMA of .rodata is no different than finding its offset, it's just a different column is all:
So here's what we know so far: the .rodata section is located at offset $315392 (= 0x04d000) into the ELF file, which will be mapped at virtual address $4509696 (= 0x44d000) at run time.
Now we need the VMA as well as the size of the symbol we're looking for:
Its VMA will (indirectly) allow us to locate it within the executable.
Its size will tell us how much data to extract once we've found the correct offset.
Step 3: Find the VMA & size of go.itab.main.Adder,main.Mather
objdump has those available for us.
First, find the symbol:
Then, get its VMA in decimal form:
And finally, get its size in decimal form:
So go.itab.main.Adder,main.Mather will be mapped at virtual address $4673856 (= 0x475140) at run time, and has a size of 40 bytes (which we already knew, as it's the size of an itab structure).
Step 4: Find & extract go.itab.main.Adder,main.Mather
We now have all the elements we need in order to locate go.itab.main.Adder,main.Mather within our binary.
Here's a reminder of what we know so far:
If $315392 (.rodata's offset) maps to $4509696 (.rodata's VMA) and go.itab.main.Adder,main.Mather's VMA is $4673856, then go.itab.main.Adder,main.Mather's offset within the executable is:
sym.offset = sym.vma - section.vma + section.offset = $4673856 - $4509696 + $315392 = $479552.
Now that we know both the offset and size of the data, we can take out good ol' dd and extract the raw bytes straight out of the executable:
It's a match! fmt.Printf("iface.tab.hash = %#x\n", iface.tab.hash) gives us 0x615f3d8a, which corresponds to the value that we've extracted from the contents of the ELF file.
Conclusion
We've reconstructed the complete itab for our iface<Mather, Adder> interface; it's all there in the executable, just waiting to be used, and already contains all the information that the runtime will need to make the interface behave as we expect.
Of course, since an itab is mostly composed of a bunch of pointers to other datastructures, we'd have to follow the virtual addresses present in the contents that we've extracted via dd in order to reconstruct the complete picture.
Speaking of pointers, we can now have a clear view of the virtual-table for iface<Mather, Adder>; here's an annotated version of the contents of go.itab.main.Adder,main.Mather:
This should already give you a pretty good idea of how dynamic dispatch is handled at run time; which is what we will look at in the next section.
Bonus
I'd imagine there must exist an easier way to do what this script does, maybe some arcane flags or an obscure gem hidden inside the binutils distribution.. who knows.
If you've got some hints, don't hesitate to say so in the issues.
In this section we'll finally cover the main feature of interfaces: dynamic dispatch. Specifically, we'll look at how dynamic dispatch works under the hood, and how much we got to pay for it.
We've already had a deeper look into most of what happens in this piece of code: how the iface<Mather, Adder> interface gets created, how it's laid out in the final exectutable, and how it ends up being loaded by the runtime.
There's only one thing left for us to look at, and that is the actual indirect method call that follows: m.Add(10, 32).
To refresh our memory, we'll zoom in on both the creation of the interface as well as on the method call itself:
Thankfully, we already have a fully annotated version of the assembly generated by the instantiation done on the first line (m := Mather(Adder{id: 6754})):
And now, here's the assembly listing for the indirect method call that follows (m.Add(10, 32)):
With the knowledge accumulated from the previous sections, these few instructions should be straightforward to understand.
Once runtime.convT2I32 has returned, AX holds i.tab, which as we know is a pointer to an itab; and more specifically a pointer to go.itab."".Adder,"".Mather in this case.
By dereferencing AX and offsetting 24 bytes forward, we reach i.tab.fun, which corresponds to the first entry of the virtual table.
Here's a reminder of what the offset table for itab looks like:
As we've seen in the previous section where we've reconstructed the final itab directly from the executable, iface.tab.fun[0] is a pointer to main.(*Adder).add, which is the compiler-generated wrapper-method that wraps our original value-receiver main.Adder.add method.
We store 10 and 32 at the top of the stack, as arguments #2 & #3.
Once runtime.convT2I32 has returned, CX holds i.data, which is a pointer to our Adder instance.
We move this pointer to the top of stack, as argument #1, to satisfy the calling convention: the receiver for a method should always be passed as the first argument.
Finally, with our stack all set up, we can do the actual call.
We'll close this section with a complete annotated assembly listing of the entire process:
We now have a clear picture of the entire machinery required for interfaces and virtual method calls to work. In the next section, we'll measure the actual cost of this machinery, in theory as well as in practice.
Once an interface has been properly instantiated, calling methods on it is nothing more than going through one more layer of indirection compared to the usual statically dispatched call (i.e. dereferencing itab.fun at the desired index).
As such, one would imagine this process to be virtually free.. and one would be kind of right, but not quite: the theory is a bit tricky, and the reality even trickier still.
The theory: quick refresher on modern CPUs
The extra indirection inherent to virtual calls is, in and of itself, effectively free for as long as it is somewhat predictable from the standpoint of the CPU. Modern CPUs are very aggressive beasts: they cache aggressively, they aggressively pre-fetch both instructions & data, they pre-execute code aggressively, they even reorder and parallelize it as they see fit. All of this extra work is done whether we want it or not, hence we should always strive not to get in the way of the CPU's efforts to be extra smart, so all of these precious cycles don't go needlessly wasted.
This is where virtual method calls can quickly become a problem.
In the case of a statically dispatched call, the CPU has foreknowledge of the upcoming branch in the program and pre-fetches the necessary instructions accordingly. This makes up for a smooth, transparent transition from one branch of the program to the other as far as performance is concerned. With dynamic dispatch, on the other hand, the CPU cannot know in advance where the program is heading: it all depends on computations whose results are, by definition, not known until run time. To counter-balance this, the CPU applies various algorithms and heuristics in order to guess where the program is going to branch next (i.e. "branch prediction").
If the processor guesses correctly, we can expect a dynamic branch to be almost as efficient as a static one, since the instructions of the landing site have already been pre-fetched into the processor's caches anyway.
If it gets things wrong, though, things can get a bit rough: first, of course, we'll have to pay for the extra indirection plus the corresponding (slow) load from main memory (i.e. the CPU is effectively stalled) to load the right instructions into the L1i cache. Even worse, we'll have to pay for the price of the CPU backtracking in its own mistakes and flushing its instruction pipeline following the branch misprediction. Another important downside of dynamic dispatch is that it makes inlining impossible by definition: one simply cannot inline what they don't know is coming.
All in all, it should, at least in theory, be very possible to end up with massive differences in performance between a direct call to an inlined function F, and a call to that same function that couldn't be inlined and had to go through some extra layers of indirection, and maybe even got hit by a branch misprediction on its way.
That's mostly it for the theory. When it comes to modern hardware, though, one should always be wary of the theory.
Let's measure this stuff.
The practice: benchmarks
First things first, some information about the CPU we're running on:
Benchmark suite A: single instance, many calls, inlined & non-inlined
For our first two benchmarks, we'll try calling a non-inlined method inside a busy-loop, on both an *Adder value and a iface<Mather, *Adder> interface:
We expect both benchmarks to run A) extremely fast and B) at almost the same speeds.
Given the tightness of the loop, we can expect both benchmarks to have their data (receiver & vtable) and instructions ("".(*id32).idNoInline) already be present in the L1d/L1i caches of the CPU for each iteration of the loop. I.e., performance should be purely CPU-bound.
BenchmarkMethodCall_interface should run a bit slower (on the nanosecond scale) though, as it has to deal with the overhead of finding & copying the right pointer from the virtual table (which is already in the L1 cache, though).
Since the CALL CX instruction has a strong dependency on the output of these few extra instructions required to consult the vtable, the processor has no choice but to execute all of this extra logic as a sequential stream, leaving any chance of instruction-level parallelization on the table.
This is ultimately the main reason why we would expect the "interface" version to run a bit slower.
We end up with the following results for the "direct" version:
And here's for the "interface" version:
The results match our expectations: the "interface" version is indeed a bit slower, with approximately 0.15 extra nanoseconds per iteration, or a ~8% slowdown. 8% might sound like a noticeable difference at first, but we have to keep in mind that A) these are nanosecond-scale measurements and B) the method being called does so little work that it magnifies even more the overhead of the call.
Looking at the number of instructions per benchmark, we see that the interface-based version has had to execute for ~14 billion more instructions compared to the "direct" version (110,979,100,648 vs. 124,467,105,161), even though both benchmarks were run for 6,000,000,000 (2,000,000,000\*3) iterations.
As we've mentioned before, the CPU cannot parallelize these extra instructions due to the CALL depending on them, which gets reflected quite clearly in the instruction-per-cycle ratio: both benchmarks end up with a similar IPC ratio (2.54 vs. 2.63) even though the "interface" version has much more work to do overall.
This lack of parallelism piles up to an extra ~3.5 billion CPU cycles for the "interface" version, which is where those extra 0.15ns that we've measured are actually spent.
Now what happens when we let the compiler inline the method call?
Two things jump out at us:
BenchmarkMethodCall_direct: Thanks to inlining, the call has been reduced to a simple pair of memory moves.
BenchmarkMethodCall_interface: Due to dynamic dispatch, the compiler has been unable to inline the call, thus the generated assembly ends up being exactly the same as before.
We won't even bother running BenchmarkMethodCall_interface since the code hasn't changed a bit.
Let's have a quick look at the "direct" version though:
As expected, this runs ridiculously fast now that the overhead of the call is gone. With ~0.34ns per op for the "direct" inlined version, the "interface" version is now ~475% slower, quite a steep drop from the ~8% difference that we've measured earlier with inlining disabled.
Notice how, with the branching inherent to the method call now gone, the CPU is able to parallelize and speculatively execute the remaining instructions much more efficiently, reaching an IPC ratio of 4.61.
Benchmark suite B: many instances, many non-inlined calls, small/big/pseudo-random iterations
For this second benchmark suite, we'll look at a more real-world-like situation in which an iterator goes through a slice of objects that all expose a common method and calls it for each object.
To better mimic reality, we'll disable inlining, as most methods called this way in a real program would most likely by sufficiently complex not to be inlined by the compiler (YMMV; a good counter-example of this is the sort.Interface interface from the standard library).
We'll define 3 similar benchmarks that just differ in the way they access this slice of objects; the goal being to simulate decreasing levels of cache friendliness: 1. In the first case, the iterator walks the array in order, calls the method, then gets incremented by the size of one object for each iteration. 1. In the second case, the iterator still walks the slice in order, but this time gets incremented by a value that's larger than the size of a single cache-line. 1. Finally, in the third case, the iterator will pseudo-randomly steps through the slice.
In all three cases, we'll make sure that the array is big enough not to fit entirely in any of the processor's caches in order to simulate (not-so-accurately) a very busy server that's putting a lot of pressure of both its CPU caches and main memory.
Here's a quick recap of the processor's attributes, we'll design the benchmarks accordingly:
Here's what the benchmark suite looks like for the "direct" version (the benchmarks marked as baseline compute the cost of retrieving the receiver in isolation, so that we can subtract that cost from the final measurements):
The benchmark suite for the "interface" version is identical, except that the array is initialized with interface values instead of pointers to the concrete type, as one would expect:
For the "direct" suite, we get the following results:
There really are no surprises here: 1. small_incr: By being extremely cache-friendly, we obtain results similar to the previous benchmark that looped over a single instance. 2. big_incr: By forcing the CPU to fetch a new cache-line at every iteration, we do see a noticeable bump in latencies, which is completely unrelated to the cost of doing the call, though: ~6ns are attributable to the baseline while the rest is a combination of the cost of dereferencing the receiver in order to get to its id field and copying around the return value. 3. random_incr: Same remarks as with big_incr, except that the bump in latencies is even more pronounced due to A) the pseudo-random accesses and B) the cost of retrieving the next index from the pre-computed array of indexes (which triggers cache misses in and of itself).
As logic would dictate, thrashing the CPU d-caches doesn't seem to influence the latency of the actual direct method call (inlined or not) by any mean, although it does make everything that surrounds it slower.
What about dynamic dispatch?
The results are extremely similar, albeit a tiny bit slower overall simply due to the fact that we're copying two quad-words (i.e. both fields of an identifier interface) out of the slice at each iteration instead of one (a pointer to id32).
The reason this runs almost as fast as its "direct" counterpart is that, since all the interfaces in the slice share a common itab (i.e. they're all iface<Mather, Adder> interfaces), their associated virtual table never leaves the L1d cache and so fetching the right method pointer at each iteration is virtually free.
Likewise, the instructions that make up the body of the main.(*id32).idNoInline method never leave the L1i cache.
One might think that, in practice, a slice of interfaces would encompass many different underlying types (and thus vtables), which would result in thrashing of both the L1i and L1d caches due to the varying vtables pushing each other out.
While that holds true in theory, these kinds of thoughts tend to be the result of years of experience using older OOP languages such as C++ that (used to, at least) encourage the use of deeply-nested hierarchies of inherited classes and virtual calls as their main tool of abstraction.
With big enough hierarchies, the number of associated vtables could sometimes get large enough to thrash the CPU caches when iterating over a datastructure holding various implementations of a virtual class (think e.g. of a GUI framework where everything is a Widget stored in a graph-like datastructure); especially so that, in C++ at least, virtual classes tend to specify quite complex behaviors, sometimes with dozen of methods, resulting in quite big vtables and even more pressure on the L1d cache.
Go, on the other hand, has very different idioms: OOP has been completely thrown out of the window, the type system flattened, and interfaces are most often used to describe minimal, constrained behaviors (a few methods at most an average, helped by the fact that interfaces are implicitly satisfied) instead of being used as an abstraction on top of a more complex, layered type hierarchy. In practice, in Go, I've found it's very rare to have to iterate over a set of interfaces that carry many different underlying types. YMMV, of course.
For the curious-minded, here's what the results of the "direct" version would have looked like with inlining enabled:
Which would have made the "direct" version around 2 to 3 times faster than the "interface" version in cases where the compiler would have been able to inline the call. Then again, as we've mentioned earlier, the limited capabilities of the current compiler with regards to inlining mean that, in practice, these kind of wins would rarely be seen. And of course, there often are times when you really don't have a choice but to resort to virtual calls anyway.
Conclusion
Effectively measuring the latency of a virtual call turned out to be quite a complex endeavor, as most of it is the direct consequence of many intertwined side-effects that result from the very complex implementation details of modern hardware.
In Go, thanks to the idioms encouraged by the design of the language, and taking into account the (current) limitations of the compiler with regards to inlining, one could effectively consider dynamic dispatch as virtually free. Still, when in doubt, one should always measure their hot paths and look at the relevant performance counters to assert with certainty whether dynamic dispatch ends up being an issue or not.
(NOTE: We will look at the inlining capabilities of the compiler in a later chapter of this book.)
This section will review some of the most common special cases that we encounter every day when dealing with interfaces.
By now you should have a pretty clear idea of how interfaces work, so we'll try and aim for conciseness here.
The datastructure for the empty interface is what you'd intuitively think it would be: an iface without an itab.
There are two reasons for that: 1. Since the empty interface has no methods, everything related to dynamic dispatch can safely be dropped from the datastructure. 1. With the virtual table gone, the type of the empty interface itself, not to be confused with the type of the data it holds, is always the same (i.e. we talk about the empty interface rather than an empty interface).
NOTE: Similar to the notation we used for iface, we'll denote the empty interface holding a type T as eface<T>
Where _type holds the type information of the value pointed to by data.
As expected, the itab has been dropped entirely.
While the empty interface could just reuse the iface datastructure (it is a superset of eface after all), the runtime chooses to distinguish the two for two main reasons: space efficiency and code clarity.
That's a 2-orders-of-magnitude difference in performance for a simple assignment operation, and
we can see that the second benchmark has to allocate 4 extra bytes at each iteration.
Clearly, some hidden heavy machinery is being set off in the second case: we need to have a look at the generated assembly.
For the first benchmark, the compiler generates exactly what you'd expect it to with regard to the assignment operation:
In the second benchmark, though, things get far more complex:
This is just the assignment, not the complete benchmark! We'll have to study this code piece by piece.
Step 1: Create the interface
This first piece of the listing instantiates the empty interface eface<uint32> that we will later assign to Eface.
It turns out that runtime.convT2I32 and runtime.convT2E32 are part of a larger family of functions whose job is to instanciate either a specific interface or the empty interface from a scalar value (or a string or slice, as special cases).
This family is composed of 10 symbols, one for each combination of (eface/iface, 16/32/64/string/slice):
(You'll notice that there is no convT2E8 nor convT2I8 function; this is due to a compiler optimization that we'll take a look at at the end of this section.)
The function initializes the _type field of the eface structure "passed" in by the caller (remember: return values are allocated by the caller on its own stack-frame) with the _type given as first parameter.
For the data field of the eface, it all depends on the value of the second parameter elem:
If elem is zero, e.data is initialized to point to runtime.zeroVal, which is a special global variable defined by the runtime that represents the zero value. We'll discuss a bit more about this special variable in the next section.
If elem is non-zero, the function allocates 4 bytes on the heap (x = mallocgc(4, t, false)), initializes the contents of those 4 bytes with the value pointed to by elem (*(*uint32)(x) = *(*uint32)(elem)), then stick the resulting pointer into e.data.
In this case, e._type holds the address of type.uint32 (LEAQ type.uint32(SB), AX), which is implemented by the standard library and whose address will only be known when linking against said stdlib:
(U denotes that the symbol is not defined in this object file, and will (hopefully) be provided by another object at link-time (i.e. the standard library in this case).)
Step 2: Assign the result (part 1)
The result of runtime.convT2E32 gets assigned to our Eface variable.. or does it?
Actually, for now, only the _type field of the returned value is being assigned to Eface._type, the data field cannot be copied over just yet.
Step 3: Assign the result (part 2) or ask the garbage collector to
The apparent complexity of this last piece is a side-effect of assigning the data pointer of the returned eface to Eface.data: since we're manipulating the memory graph of our program (i.e. which part of memory holds references to which part of memory), we may have to notify the garbage collector of this change, just in case a garbage collection were to be currently running in the background.
This is known as a write barrier, and is a direct consequence of Go's concurrent garbage collector.
Don't worry if this sounds a bit vague for now; the next chapter of this book will offer a thorough review of garbage collection in Go.
For now, it's enough to remember that when we see some assembly code calling into runtime.gcWriteBarrier, it has to do with pointer manipulation and notifying the garbage collector.
All in all, this final piece of code can do one of two things:
If the write-barrier is currently inactive, it assigns ret.data to Eface.data (MOVQ AX, 8(DX)).
If the write-barrier is active, it politely asks the garbage-collector to do the assignment on our behalf
(LEAQ 8(DX), DI + CALL runtime.gcWriteBarrier(SB)).
(Once again, try not to worry too much about this for now.)
Voila, we've got a complete interface holding a simple scalar type (uint32).
Conclusion
While sticking a scalar value into an interface is not something that happens that often in practice, it can be a costly operation for various reasons, and as such it's important to be aware of the machinery behind it.
Speaking of cost, we've mentioned that the compiler implements various tricks to avoid allocating in some specific situations; we'll close this section with a quick look at 3 of those tricks.
Interface trick 1: Byte-sized values
We notice that in the case of a byte-sized value, the compiler avoids the call to runtime.convT2E/runtime.convT2I and the associated heap allocation, and instead re-uses the address of a global variable exposed by the runtime that already holds the 1-byte value we're looking for: LEAQ runtime.staticbytes(SB), R8.
Using the right offset into this array, the compiler can effectively avoid an extra heap allocation and still reference any value representable as a single byte.
Something feels wrong here, though.. can you tell?
The generated code still embeds all the machinery related to the write-barrier, even though the pointer we're manipulating holds the address of a global variable whose lifetime is the same as the entire program's anyway.
I.e. runtime.staticbytes can never be garbage collected, no matter which part of memory holds a reference to it or not, so we shouldn't have to pay for the overhead of a write-barrier in this case.
Interface trick 2: Static inference
We can see from the generated assembly that the compiler completely optimizes out the call to runtime.convT2E64, and instead directly constructs the empty interface by loading the address of an autogenerated global variable that already holds the value we're looking for: LEAQ "".statictmp_0(SB), SI (note the (SB) part, indicating a global variable).
We can better visualize what's going on using the script that we've hacked up earlier: dump_sym.sh.
As expected, main.statictmp_0 is a 8-byte variable whose value is 0x000000000000002a, i.e. $42.
Interface trick 3: Zero-values
First, notice how we make use of uint32(i - i) instead of uint32(0) to prevent the compiler from falling back to optimization #2 (static inference).
(Sure, we could just have declared a global zero variable and the compiler would had been forced to take the conservative route too.. but then again, we're trying to have some fun here. Don't be that guy.)
The generated code now looks exactly like the normal, allocating case.. and still, it doesn't allocate. What's going on?
This ends our little tour of optimizations. We'll close this section with a summary of all the benchmarks that we've just looked at:
As we've just seen, the runtime.convT2* family of functions avoids a heap allocation when the data to be held by the resulting interface happens to reference a zero-value.
This optimization is not specific to interfaces and is actually part of a broader effort by the Go runtime to make sure that, when in need of a pointer to a zero-value, unnecessary allocations are avoided by taking the address of a special, always-zero variable exposed by the runtime.
As expected.
Note the //go:linkname directive which allows us to reference an external symbol:
The //go:linkname directive instructs the compiler to use “importpath.name” as the object file symbol name for the variable or function declared as “localname” in the source code. Because this directive can subvert the type system and package modularity, it is only enabled in files that have imported "unsafe".
In a similar vein as zero-values, a very common trick in Go programs is to rely on the fact that instanciating an object of size 0 (such as struct{}{}) doesn't result in an allocation.
The official Go specification (linked at the end of this chapter) ends on a note that explains this:
A struct or array type has size zero if it contains no fields (or elements, respectively) that have a size greater than zero. Two distinct zero-size variables may have the same address in memory.
The "may" in "may have the same address in memory" implies that the compiler doesn't guarantee this fact to be true, although it has always been and continues to be the case in the current implementation of the official Go compiler (gc).
If we'd like to know what hides behind this address, we can simply have a peek inside the binary:
And if we'd rather be really, really sure indeed:
There really is nothing special about interface composition, it merely is syntastic sugar exposed by the compiler.
As usual, the compiler generates the corresponding itab for iface<Mather, *Calculator>:
We can see from the relocation directives that the virtual table generated by the compiler holds both the methods of Adder as well as those belonging to Subber, as we'd expect:
Like we said, there's no secret sauce when it comes to interface composition.
On an unrelated note, this little program demonstrates something that we had not seen up until now: since the generated itab is specifically tailored to a pointer to a Constructor, as opposed to a concrete value, this fact gets reflected both in its symbol-name (go.itab.*"".Calculator,"".Mather) as well as in the _type that it embeds (type.*"".Calculator).
This is consistent with the semantics used for naming method symbols, like we've seen earlier at the beginning of this chapter.
We'll close this chapter by looking at type assertions, both from an implementation and a cost standpoint.
Here's the annotated assembly listing for j = Eface.(uint32):
Nothing surprising in there: the code compares the address held by Eface._type with the address of type.uint32, which, as we've seen before, is the global symbol exposed by the standard library that holds the content of the _type structure which describes an uint32.
If the _type pointers match, then all is good and we're free to assign *Eface.data to j; otherwise, we call runtime.panicdottypeE to throw a panic message that precisely describes the mismatch.
What about performance?
Well, let's see what we've got here: a bunch of MOVs from main memory, a very predictable branch and, last but not least, a pointer dereference (j = *Eface.data) (which is only there because we've initialized our interface with a concrete value in the first place, otherwise we could just have copied the Eface.data pointer directly).
It's not even worth micro-benchmarking this, really. Similarly to the overhead of dynamic dispatch that we've measured earlier, this is in and of itself, in theory, almost free. How much it'll really cost you in practice will most likely be a matter of how your code-path is designed with regard to cache-friendliness & al. A simple micro-benchmark would probably be too skewed to tell us anything useful here, anyway.
All in all, we end up with the same old advice as usual: measure for your specific use case, check your processor's performance counters, and assert whether or not this has a visible impact on your hot path. It might. It might not. It most likely doesn't.
This quite simple type-switch statement translates into the following assembly (annotated):
Once again, if you meticulously step through the generated code and carefully read the corresponding annotations, you'll find that there's no dark magic in there. The control flow might look a bit convoluted at first, as it jumps back and forth a lot, but other than it's a pretty faithful rendition of the original Go code.
There are quite a few interesting things to note, though.
Note 1: Layout
First, notice the high-level layout of the generated code, which matches pretty closely the original switch statement: 1. We find an initial block of instructions that loads the _type of the variable we're interested in, and checks for nil pointers, just in case. 1. Then, we get N logical blocks that each correspond to one of the cases described in the original switch statement. 1. And finally, one last block defines a kind of indirect jump table that allows the control flow to jump from one case to the next while making sure to properly reset dirty registers on the way.
While obvious in hindsight, that second point is pretty important, as it implies that the number of instructions generated by a type-switch statement is purely a factor of the number of cases that it describes. In practice, this could lead to surprising performance issues as, for example, a massive type-switch statement with plenty of cases could generate a ton of instructions and end up thrashing the L1i cache if used on the wrong path.
Another interesting fact regarding the layout of our simple switch-statement above is the order in which the cases are set up in the generated code. In our original Go code, case uint16 came first, followed by case uint32. In the assembly generated by the compiler, though, their orders have been reversed, with case uint32 now being first and case uint16 coming in second.
That this reordering is a net win for us in this particular case is nothing but mere luck, AFAICT. In fact, if you take the time to experiment a bit with type-switches, especially ones with more than two cases, you'll find that the compiler always shuffles the cases using some kind of deterministic heuristics.
What those heuristics are, I don't know (but as always, I'd love to if you do).
Note 2: O(n)
Second, notice how the control flow blindly jumps from one case to the next, until it either lands on one that evaluates to true or finally reaches the end of the switch statement.
Once again, while obvious when one actually stops to think about it ("how else could it work?"), this is easy to overlook when reasoning at a higher-level. In practice, this means that the cost of evaluating a type-switch statement grows linearly with its number of cases: it's O(n).
Likewise, evaluating a type-switch statement with N cases effectively has the same time-complexity as evaluating N type-assertions. As we've said, there's no magic here.
With all its extra cases, the second type-switch does take almost twice as long per iteration indeed.
As an interesting exercise for the reader, try adding a case uint32 in either one of the benchmarks above (anywhere), you'll see their performances improve drastically:
Using all the tools and knowledge that we've gathered during this chapter, you should be able to explain the rationale behind the numbers. Have fun!
Note 3: Type hashes & pointer comparisons
Finally, notice how the type comparisons in each cases are always done in two phases: 1. The types' hashes (_type.hash) are compared, and then 2. if they match, the respective memory-addresses of each _type pointers are compared directly.
Since each _type structure is generated once by the compiler and stored in a global variable in the .rodata section, we are guaranteed that each type gets assigned a unique address for the lifetime of the program.
In that context, it makes sense to do this extra pointer comparison in order to make sure that the successful match wasn't simply the result of a hash collision.. but then this raises an obvious question: why not just compare the pointers directly in the first place, and drop the notion of type hashes altogether? Especially when simple type assertions, as we've seen earlier, don't use type hashes at all. The answer is I don't have the slightest clue, and certainly would love some enlightment on this. As always, feel free to open an issue if you know more.
That's it for interfaces.
I hope this chapter has given you most of the answers you were looking for when it comes to interfaces and their innards. Most importantly, it should have provided you with all the necessary tools and skills required to dig further whenever you'd need to.
If you have any questions or suggestions, don't hesitate to open an issue with the chapter2: prefix!
Consider the following code ():
The runtime.panicwrap function, which throws a panic if the wrapper's receiver is nil, is pretty self-explanatory; here's its complete listing for reference ():
iface is the root type that represents an interface within the runtime ().
Its definition goes like this:
We can prove that with a few lines of code ():
One could even visualize the resulting heap allocation using a simple benchmark ():
itab is defined thusly ():
As we said above, the _type structure gives a complete description of a Go type.
It's defined as such ():
The nameOff & typeOff types are int32 offsets into the metadata embedded into the final executable by the linker. This metadata is loaded into runtime.moduledata structures at run time (), which should look fairly similar if you've ever had to look at the content of an ELF file.
The runtime provide helpers that implement the necessary logic for following these offsets through the moduledata structures, such as e.g. resolveNameOff () and resolveTypeOff ():
Finally, here's the interfacetype structure ():
Consider the following program ():
Note the dupok directive, which tells the linker that it is legal for this symbol to appear multiple times at link-time: the linker will have to arbitrarily choose one of them over the others.
What makes the Go authors think that this symbol might end up duplicated, I'm not sure. Feel free to file an issue if you know more.
[UPDATE: We've discussed about this matter in .]
These two pointers are the two arguments that we pass into runtime.convT2I32, which will apply the final touches of glue to create and return our complete interface.
Let's have a closer look at it ():
This process is quite straightforward overall, although the 3rd step does involve some tricky implementation details in this specific case, which are caused by the fact that our Adder type is effectively a scalar type.
We'll look at the interactions of scalar types and interfaces in more details in the section about .
This certainly does look like a clear-cut victory.. but is it, really? Maybe we've just dumped 40 totally random, unrelated bytes? Who knows?
There's at least one way to be sure: let's compare the type hash found in our binary dump (at offset 0x10+4 -> 0x615f3d8a) with the one loaded by the runtime ():
Without surprise, the virtual table for iface<Mather, Adder> holds two method pointers: main.(*Adder).add and main.(*Adder).sub.
Well, actually, this is a bit surprising: we've never defined these two methods to have pointer receivers.
The compiler has generated these wrapper methods on our behalf (as we've described in the ) because it knows that we're going to need them: since an interface can only hold pointers, and since our Adder implementation of said interface only provides methods with value-receivers, we'll have to go through a wrapper at some point if we're going to call either of these methods via the virtual table of the interface.
I've hacked up a generic bash script that you can use to dump the contents of any symbol in any section of an ELF file ():
Let's have a look back at our code from earlier ():
As we've seen, the implementation of interfaces delegates most of the work on both the compiler and the linker. From a performance standpoint, this is obviously very good news: we effectively want to relieve the runtime from as much work as possible.
There do exist some specific cases where instantiating an interface may also require the runtime to get to work (e.g. the runtime.convT2* family of functions), though they are not so prevalent in practice.
We'll learn more about these edge cases in the . In the meantime, we'll concentrate purely on the overhead of virtual method calls and ignore the one-time costs related to instantiation.
We'll define the interface used for our benchmarks as such ():
eface is the root type that represents the empty interface within the runtime ().
Its definition goes like this:
Earlier in this chapter (), we've mentioned that even storing a simple scalar type such as an integer into an interface will result in a heap allocation. It's time we see why, and how.
Consider these two benchmarks ():
We've already studied similar code in the section about creating interfaces (), except that this code was calling runtime.convT2I32 instead of runtime.convT2E32 here; nonetheless, this should look very familiar.
All of these functions do almost the exact same thing, they only differ in the type of their return value (iface vs. eface) and the size of the memory that they allocate on the heap.
Let's take a look at e.g. runtime.convT2E32 more closely ():
Consider this benchmark that instanciates an eface<uint8> ():
runtime.staticbytes can be found in and looks like this:
Consider this benchmark that instanciates an eface<uint64> from a value known at compile time ():
For this final trick, consider the following benchmark that instanciates an eface<uint32> from a zero-value ():
As we've mentioned earlier back when we were dissecting runtime.convT2E32, the allocation here can be optimized out using a trick similar to #1 (byte-sized values): when some code needs to reference a variable that holds a zero-value, the compiler simply gives it the address of a global variable exposed by the runtime whose value is always zero.
Similarly to runtime.staticbytes, we can find this variable in the runtime code ():
We can confirm this with a simple program ():
As usual, we can confirm this with a simple program ():
Then it's just a matter of finding this runtime.zerobase variable within the runtime source code ():
Consider the following program ():
Consider this short program ():
runtime.panicdottypeE is a very simple function that does no more than you'd expect ():
Type-switches are a bit trickier, of course. Consider the following code ():
It's easy to confirm this with a bunch of benchmarks ():
Speaking of type hashes, how is it that we know that $-800397251 corresponds to type.uint32.hash and $-269349216 to type.uint16.hash, you might wonder? The hard way, of course ():
