How fast does go compiler

I used to do web dev in Scala, but waiting for the sleepy compiler is one of the reasons is switched to Go. If the compiler catches bugs that would otherwise only be found at run time, then the additional compile time pays for itself many times over in terms of productivity.

Thaxll on Dec 11, root parent next [—]. It has yet to be proven, yes Rust catches more bugs than other language but is it worth the slow compile time? I'm not sure. I think he is referring to situation when compiler both catches errors at compile-time and is fast. After all the validation part happening in the fronted is rarely the most resource consuming thing that compiler does.

And I think rapsey is referring to the fact that a compiler with a more powerful type system allows you to encode more logic in your types. This, in turn, means it will catch more errors at compile time at the cost of longer compile times.

Yes, but I think the OP referring to Go as he dont want one or the other. He Wants both! And Go being near no-compiling time meant that best of both world From his perspective. Well it can run time during testing and run time in production.

From my experience in Java I have caught quite a few bug at run time in testing. And it is not that bad. I see you've never imported the Kubernetes client library.

What they have going for them is not depending on LLVM. F has a "slow" compiler too. That's just part of the tradeoff; though obviously you can optimize within those bounds. Not technically inviolable, but practically so. And while the F compiler is indeed faster than rustc, it's not apples-to-apples. I don't think this is true. There are other factors as well, such as the efficiency of the compiler--the same C compiler implemented in C and compiled with an advanced C compiler will handily beat a C compiler written in Python and executed on CPython.

But to your point, all-else-equal, a program in a language with an advanced type system takes longer to compile than a simpler type system. I mention this at the end of my comment, but yes the second very significant factor is the nature of transformation. Native compilers must do significantly more transformation than other compilers, e. F CLR compiler. This is doubly so if you request optimized output but that's probably not the case in this discussion. NET 1. Naturally Rust could offer an interpreter of some sort, however it still isn't there today, so we got to use what is available.

Or just interpret MIR directly. Should checkout the Ocaml compiler. It is wicked fast. LLVM seems like a big blocker for fast compiles, although I suspect Rust may additionally need some higher-level optimisation passes. Possibly not, but there does seem to be strong correlation between languages using LLVM and long compile times. Perhaps Jai is an exception, but it's hard to know how or why that is given that he has not released his language.

This makes sense since if you have optimizations off, you only have to do codegen. If you are using LLVM for codegen, then you have to codegen twice! See Developing modules for guides on managing dependencies with modules. Packages within modules should maintain backward compatibility as they evolve, following the import compatibility rule :. The Go 1 compatibility guidelines are a good reference here: don't remove exported names, encourage tagged composite literals, and so on.

If different functionality is required, add a new name instead of changing an old one. Modules codify this with semantic versioning and semantic import versioning. If a break in compatibility is required, release a module at a new major version.

This preserves the import compatibility rule: packages in different major versions of a module have distinct paths. As in all languages in the C family, everything in Go is passed by value. That is, a function always gets a copy of the thing being passed, as if there were an assignment statement assigning the value to the parameter. For instance, passing an int value to a function makes a copy of the int , and passing a pointer value makes a copy of the pointer, but not the data it points to.

See a later section for a discussion of how this affects method receivers. Map and slice values behave like pointers: they are descriptors that contain pointers to the underlying map or slice data.

Copying a map or slice value doesn't copy the data it points to. Copying an interface value makes a copy of the thing stored in the interface value. If the interface value holds a struct, copying the interface value makes a copy of the struct.

If the interface value holds a pointer, copying the interface value makes a copy of the pointer, but again not the data it points to. Note that this discussion is about the semantics of the operations. Actual implementations may apply optimizations to avoid copying as long as the optimizations do not change the semantics. Almost never. Pointers to interface values arise only in rare, tricky situations involving disguising an interface value's type for delayed evaluation.

It is a common mistake to pass a pointer to an interface value to a function expecting an interface. The compiler will complain about this error but the situation can still be confusing, because sometimes a pointer is necessary to satisfy an interface.

The insight is that although a pointer to a concrete type can satisfy an interface, with one exception a pointer to an interface can never satisfy an interface. The printing function fmt. Fprintf takes as its first argument a value that satisfies io. Writer —something that implements the canonical Write method.

Thus we can write. Even so, it's almost certainly a mistake if the value is a pointer to an interface; the result can be confusing. For programmers unaccustomed to pointers, the distinction between these two examples can be confusing, but the situation is actually very simple.

When defining a method on a type, the receiver s in the above examples behaves exactly as if it were an argument to the method. Whether to define the receiver as a value or as a pointer is the same question, then, as whether a function argument should be a value or a pointer.

There are several considerations. First, and most important, does the method need to modify the receiver? If it does, the receiver must be a pointer. Slices and maps act as references, so their story is a little more subtle, but for instance to change the length of a slice in a method the receiver must still be a pointer.

In the examples above, if pointerMethod modifies the fields of s , the caller will see those changes, but valueMethod is called with a copy of the caller's argument that's the definition of passing a value , so changes it makes will be invisible to the caller. By the way, in Java method receivers are always pointers, although their pointer nature is somewhat disguised and there is a proposal to add value receivers to the language.

It is the value receivers in Go that are unusual. Second is the consideration of efficiency. If the receiver is large, a big struct for instance, it will be much cheaper to use a pointer receiver.

Next is consistency. If some of the methods of the type must have pointer receivers, the rest should too, so the method set is consistent regardless of how the type is used. See the section on method sets for details. For types such as basic types, slices, and small structs , a value receiver is very cheap so unless the semantics of the method requires a pointer, a value receiver is efficient and clear. In short: new allocates memory, while make initializes the slice, map, and channel types.

See the relevant section of Effective Go for more details. The sizes of int and uint are implementation-specific but the same as each other on a given platform. For portability, code that relies on a particular size of value should use an explicitly sized type, like int On bit machines the compilers use bit integers by default, while on bit machines integers have 64 bits.

Historically, this was not always true. On the other hand, floating-point scalars and complex types are always sized there are no float or complex basic types , because programmers should be aware of precision when using floating-point numbers. The default type used for an untyped floating-point constant is float For a float32 variable initialized by an untyped constant, the variable type must be specified explicitly in the variable declaration:.

From a correctness standpoint, you don't need to know. Each variable in Go exists as long as there are references to it. The storage location chosen by the implementation is irrelevant to the semantics of the language. The storage location does have an effect on writing efficient programs. When possible, the Go compilers will allocate variables that are local to a function in that function's stack frame. However, if the compiler cannot prove that the variable is not referenced after the function returns, then the compiler must allocate the variable on the garbage-collected heap to avoid dangling pointer errors.

Also, if a local variable is very large, it might make more sense to store it on the heap rather than the stack. In the current compilers, if a variable has its address taken, that variable is a candidate for allocation on the heap. However, a basic escape analysis recognizes some cases when such variables will not live past the return from the function and can reside on the stack. The Go memory allocator reserves a large region of virtual memory as an arena for allocations.

This virtual memory is local to the specific Go process; the reservation does not deprive other processes of memory. A description of the atomicity of operations in Go can be found in the Go Memory Model document. These packages are good for simple tasks such as incrementing reference counts or guaranteeing small-scale mutual exclusion. For higher-level operations, such as coordination among concurrent servers, higher-level techniques can lead to nicer programs, and Go supports this approach through its goroutines and channels.

For instance, you can structure your program so that only one goroutine at a time is ever responsible for a particular piece of data. That approach is summarized by the original Go proverb ,. See the Share Memory By Communicating code walk and its associated article for a detailed discussion of this concept. Whether a program runs faster with more CPUs depends on the problem it is solving.

The Go language provides concurrency primitives, such as goroutines and channels, but concurrency only enables parallelism when the underlying problem is intrinsically parallel. Problems that are intrinsically sequential cannot be sped up by adding more CPUs, while those that can be broken into pieces that can execute in parallel can be sped up, sometimes dramatically.

Sometimes adding more CPUs can slow a program down. In practical terms, programs that spend more time synchronizing or communicating than doing useful computation may experience performance degradation when using multiple OS threads. This is because passing data between threads involves switching contexts, which has significant cost, and that cost can increase with more CPUs. For instance, the prime sieve example from the Go specification has no significant parallelism although it launches many goroutines; increasing the number of threads CPUs is more likely to slow it down than to speed it up.

For more detail on this topic see the talk entitled Concurrency is not Parallelism. How can I control the number of CPUs? Programs with the potential for parallel execution should therefore achieve it by default on a multiple-CPU machine.

To change the number of parallel CPUs to use, set the environment variable or use the similarly-named function of the runtime package to configure the run-time support to utilize a different number of threads. Setting it to 1 eliminates the possibility of true parallelism, forcing independent goroutines to take turns executing.

Go's goroutine scheduler is not as good as it needs to be, although it has improved over time. In the future, it may better optimize its use of OS threads. Goroutines do not have names; they are just anonymous workers. They expose no unique identifier, name, or data structure to the programmer. Some people are surprised by this, expecting the go statement to return some item that can be used to access and control the goroutine later.

The fundamental reason goroutines are anonymous is so that the full Go language is available when programming concurrent code. By contrast, the usage patterns that develop when threads and goroutines are named can restrict what a library using them can do. Here is an illustration of the difficulties. Once one names a goroutine and constructs a model around it, it becomes special, and one is tempted to associate all computation with that goroutine, ignoring the possibility of using multiple, possibly shared goroutines for the processing.

Moreover, experience with libraries such as those for graphics systems that require all processing to occur on the "main thread" has shown how awkward and limiting the approach can be when deployed in a concurrent language. The very existence of a special thread or goroutine forces the programmer to distort the program to avoid crashes and other problems caused by inadvertently operating on the wrong thread.

For those cases where a particular goroutine is truly special, the language provides features such as channels that can be used in flexible ways to interact with it. Doing so would allow a method to modify the contents of the value inside the interface, which is not permitted by the language specification. Even in cases where the compiler could take the address of a value to pass to the method, if the method modifies the value the changes will be lost in the caller.

As an example, if the Write method of bytes. Buffer used a value receiver rather than a pointer, this code:. This is almost never the desired behavior. One might mistakenly expect to see a, b, c as the output.

What you'll probably see instead is c, c, c. This is because each iteration of the loop uses the same instance of the variable v , so each closure shares that single variable. When the closure runs, it prints the value of v at the time fmt. Println is executed, but v may have been modified since the goroutine was launched.

To help detect this and other problems before they happen, run go vet. To bind the current value of v to each closure as it is launched, one must modify the inner loop to create a new variable each iteration. One way is to pass the variable as an argument to the closure:. In this example, the value of v is passed as an argument to the anonymous function.

That value is then accessible inside the function as the variable u. Even easier is just to create a new variable, using a declaration style that may seem odd but works fine in Go:. This behavior of the language, not defining a new variable for each iteration, may have been a mistake in retrospect. It may be addressed in a later version but, for compatibility, cannot change in Go version 1. There is no ternary testing operation in Go.

You may use the following to achieve the same result:. The reason? The if-else form, although longer, is unquestionably clearer. A language needs only one conditional control flow construct. Put all the source files for the package in a directory by themselves. Source files can refer to items from different files at will; there is no need for forward declarations or a header file.

Other than being split into multiple files, the package will compile and test just like a single-file package. Inside that file, import "testing" and write functions of the form. Run go test in that directory. That script finds the Test functions, builds a test binary, and runs it. See the How to Write Go Code document, the testing package and the go test subcommand for more details. Go's standard testing package makes it easy to write unit tests, but it lacks features provided in other language's testing frameworks such as assertion functions.

An earlier section of this document explained why Go doesn't have assertions, and the same arguments apply to the use of assert in tests. Proper error handling means letting other tests run after one has failed, so that the person debugging the failure gets a complete picture of what is wrong.

It is more useful for a test to report that isPrime gives the wrong answer for 2, 3, 5, and 7 or for 2, 4, 8, and 16 than to report that isPrime gives the wrong answer for 2 and therefore no more tests were run.

The programmer who triggers the test failure may not be familiar with the code that fails. Time invested writing a good error message now pays off later when the test breaks. A related point is that testing frameworks tend to develop into mini-languages of their own, with conditionals and controls and printing mechanisms, but Go already has all those capabilities; why recreate them?

We'd rather write tests in Go; it's one fewer language to learn and the approach keeps the tests straightforward and easy to understand. If the amount of extra code required to write good errors seems repetitive and overwhelming, the test might work better if table-driven, iterating over a list of inputs and outputs defined in a data structure Go has excellent support for data structure literals.

The work to write a good test and good error messages will then be amortized over many test cases. The standard Go library is full of illustrative examples, such as in the formatting tests for the fmt package. There is no clear criterion that defines what is included because for a long time, this was the only Go library. There are criteria that define what gets added today, however.

New additions to the standard library are rare and the bar for inclusion is high. Code included in the standard library bears a large ongoing maintenance cost often borne by those other than the original author , is subject to the Go 1 compatibility promise blocking fixes to any flaws in the API , and is subject to the Go release schedule , preventing bug fixes from being available to users quickly.

Most new code should live outside of the standard library and be accessible via the go tool 's go get command. Such code can have its own maintainers, release cycle, and compatibility guarantees. Users can find packages and read their documentation at godoc.

But we encourage most new code to live elsewhere. There are several production compilers for Go, and a number of others in development for various platforms. The default compiler, gc , is included with the Go distribution as part of the support for the go command. Gc was originally written in C because of the difficulties of bootstrapping—you'd need a Go compiler to set up a Go environment.

But things have advanced and since the Go 1. The compiler was converted from C to Go using automatic translation tools, as described in this design document and talk. Thus the compiler is now "self-hosting", which means we needed to face the bootstrapping problem. The solution is to have a working Go installation already in place, just as one normally has with a working C installation. The story of how to bring up a new Go environment from source is described here and here.

At the beginning of the project we considered using LLVM for gc but decided it was too large and slow to meet our performance goals. More important in retrospect, starting with LLVM would have made it harder to introduce some of the ABI and related changes, such as stack management, that Go requires but are not part of the standard C setup.

A new LLVM implementation is starting to come together now, however. Go turned out to be a fine language in which to implement a Go compiler, although that was not its original goal. Not being self-hosting from the beginning allowed Go's design to concentrate on its original use case, which was networked servers.

Had we decided Go should compile itself early on, we might have ended up with a language targeted more for compiler construction, which is a worthy goal but not the one we had initially.

Although gc does not use them yet? Again due to bootstrapping issues, the run-time code was originally written mostly in C with a tiny bit of assembler but it has since been translated to Go except for some assembler bits.

Gccgo 's run-time support uses glibc. The gccgo compiler implements goroutines using a technique called segmented stacks, supported by recent modifications to the gold linker. Gollvm similarly is built on the corresponding LLVM infrastructure.

The linker in the gc toolchain creates statically-linked binaries by default. All Go binaries therefore include the Go runtime, along with the run-time type information necessary to support dynamic type checks, reflection, and even panic-time stack traces.

A simple C "hello, world" program compiled and linked statically using gcc on Linux is around kB, including an implementation of printf. An equivalent Go program using fmt. Printf weighs a couple of megabytes, but that includes more powerful run-time support and type and debugging information. This can reduce the binary size substantially. The presence of an unused variable may indicate a bug, while unused imports just slow down compilation, an effect that can become substantial as a program accumulates code and programmers over time.

For these reasons, Go refuses to compile programs with unused variables or imports, trading short-term convenience for long-term build speed and program clarity. Still, when developing code, it's common to create these situations temporarily and it can be annoying to have to edit them out before the program will compile.

Some have asked for a compiler option to turn those checks off or at least reduce them to warnings. Such an option has not been added, though, because compiler options should not affect the semantics of the language and because the Go compiler does not report warnings, only errors that prevent compilation.

There are two reasons for having no warnings. First, if it's worth complaining about, it's worth fixing in the code. And if it's not worth fixing, it's not worth mentioning. Second, having the compiler generate warnings encourages the implementation to warn about weak cases that can make compilation noisy, masking real errors that should be fixed. It's easy to address the situation, though.

In a time-sharing system the operating systems must constantly switch the attention of the CPU between these processes by recording the state of the current process, then restoring the state of another.

First is the kernel needs to store the contents of all the CPU registers for that process, then restore the values for another process. Finally there is the cost of the operating system context switch, and the overhead of the scheduler function to choose the next process to occupy the CPU. There are a surprising number of registers in a modern processor.

I have difficulty fitting them on one slide, which should give you a clue how much time it takes to save and restore them. This lead to the development of threads, which are conceptually the same as processes, but share the same memory space. As threads share address space, they are lighter than processes so are faster to create and faster to switch between. Goroutines are cooperatively scheduled, rather than relying on the kernel to manage their time sharing. The switch between goroutines only happens at well defined points, when an explicit call is made to the Go runtime scheduler.

The thread, depicted by the arrow, starts on the left in the ReadFile function. It encounters os. Open , which blocks the thread while waiting for the file operation to complete, so the scheduler switches the thread to the goroutine on the right hand side.

Execution continues until the read from the c chan blocks, and by this time the os. Open call has completed so the scheduler switches the thread back the left hand side and continues to the file. Read function, which again blocks on file IO. The scheduler switches the thread back to the right hand side for another channel operation, which has unblocked during the time the left hand side was running, but it blocks again on the channel send.

Finally the thread switches back to the left hand side as the Read operation has completed and data is available. This slide shows the low level runtime. Syscall function which is the base for all functions in the os package. This allows the runtime to spin up a new thread which will service other goroutines while this current thread blocked.

This results in relatively few operating system threads per Go process, with the Go runtime taking care of assigning a runnable Goroutine to a free operating system thread. In the previous section I discussed how goroutines reduce the overhead of managing many, sometimes hundreds of thousands of concurrent threads of execution. There is another side to the goroutine story, and that is stack management, which leads me to my final topic.

This is a diagram of the memory layout of a process. The key thing we are interested is the location of the heap and the stack. Traditionally inside the address space of a process, the heap is at the bottom of memory, just above the program text and grows upwards.

Because the heap and stack overwriting each other would be catastrophic, the operating system usually arranges to place an area of unwritable memory between the stack and the heap to ensure that if they did collide, the program will abort. This is called a guard page, and effectively limits the stack size of a process, usually in the order of several megabytes.

The downside is that as the number of threads in your program increases, the amount of available address space is reduced. Instead of using guard pages, the Go compiler inserts a check as part of every function call to check if there is sufficient stack for the function to run.

If there is not, the runtime can allocate more stack space. Because of this check, a goroutines initial stack can be made much smaller, which in turn permits Go programmers to treat goroutines as cheap resources. When G calls to H there is not enough space for H to run, so the runtime allocates a new stack frame from the heap, then runs H on that new stack segment. When H returns, the stack area is returned to the heap before returning to G.

This method of managing the stack works well in general, but for certain types of code, usually recursive code, it can cause the inner loop of your program to straddle one of these stack boundaries. For example, in the inner loop of your program, function G may call H many times in a loop,. Instead of adding and removing additional stack segments, if the stack of a goroutine is too small, a new, larger, stack will be allocated.

After the first call to H the stack will be large enough that the check for available stack space will always succeed. These are the five features that I chose to speak about today, but they are by no means the only things that makes Go a fast programming language, just as there more that three reasons that people cite as their reason to learn Go.

For example, the way the runtime multiplexes goroutines onto threads would not be nearly as efficient without growable stacks. Inlining reduces the cost of the stack size check by combining smaller functions into larger ones.

Escape analysis reduces the pressure on the garbage collector by automatically moving allocations from the heap to the stack. Good afternoon. My name is David. Why are people choosing to use Go? When people talk about their decision to learn Go, or use it in their product, they have a variety of answers, but there always three that are at the top of their list These are the top three.

The first, Concurrency. Ease of deployment. This leaves Performance. I believe an important reason why people choose to use Go is because it is fast. I will also share with you the details of how Go implements these features. Why is this important? Memory is cheap and plentiful, why should this overhead matter?

This is a graph showing CPU clock speed vs memory bus speed. Notice how the gap between CPU clock speed and memory bus speed continues to widen.