I have compiled GCC from source but I can't seem to fully understand the utility of gcc compiling itself three times.
What benefit does this serve ?
This answer says:
Build new version of GCC with existing C compiler
re-build new version of GCC with the one you just built
(optional) repeat step 2 for verification purposes.
Now my question is that once the first step is complete and the compiler is built why waste time rebuilding it ?
Is it just for verification ? If so, it seems pretty wasteful.
Things get more complicated over here,
The build for this is more complex than for prior packages, because
you’re sending more information into the configure script and the make
targets aren’t standard.
I mean the whole compiler is written in C right, so why not just do everything in one pass ?
What is the use of the 3-phase bootstrap ?
Thanks in advance.
Stage 2. and 3. are a good test for the compiler itself: If it can compile itself (and usually also some libraries like libgcc and libstdc++-v3) then it can chew non-trivial projects.
In stage 2. and 3., you can generate the compiler with different options, for example without optimization (-O0) or with optimization turned on (-O2). As the output / side effects of a program should not depend on the optimization level used, either version of the compiler must produce the same binary for the same source file, even though the two compilers are binary very different. This is yet another (run-time test) for the compiler.
If you prefer non-bootstrap for some reason, configure --disable-bootstrap.
Considering the question from an information theory perspective, the first stage in a three stage compilation of a compiler does not produce a compiler. It produces a hypothesis that requires experimental verification. The sign of a good compiler distribution package is that it will produce, out of the box and without further work for the system administrator or compiler developer, a working compiler of the distribution's version and with the desired features of that version of that brand of compiler.
Making that happen is not simple. Consider the variables in the target environment.
Target operating system brand
Operating system version
Operating system settings
Shell environment variables
Availability of headers for inclusion
Availability of libraries for linking
Settings passed to the build process
Architecture of the target processing unit
Number of processing units
Bus architecture
Other characteristics of the execution model
Mistakes the developers of the compiler might make
Mistakes the person building the compiler might make
In the GNU compiler tool set, and in many tarball distributions, the program "configure" attempts to produce a build configuration that adapts to as many of the permutations of these as is reasonably possible. The completion without error or warning from configure is not a guarantee that the compiler will function. Furthermore, and more importantly for this question, the completion of the build is no guarantee either.
The newly built compiler may function for HelloWorld.c but not for a collection of a thousand source files in a multi-project, multi-repository collection of software called, "Intelligent Interplanetary Control and Acquisition System."
Stage two and three are reasonable attempts at checking at least some of the compiler capabilities, since the compiler source itself is handy and demands quite a bit out of the hypothetically working compiler just built.
It is important to understand that the result of stage one and the result of stage two will not match. Their executables and other built artifacts are results from two different compilers. The stage one result is compiled with whatever the build system found in one of the directories listed in the "PATH" variable to compile C and C++ source code. The stage two result is compiled with the hypothetically working new compiler. The interesting probabilistic consideration is this:
If the result of using stage one's result to compile the compiler again equals exactly the result of using stage two's result to compile the compiler a third time, then both are likely correct for at least the features that the compiler's source code requires.
That last sentence may need to be reread a dozen times. Its actually a simple idea, but the redundancy of the verb compile and noun compiler can tie a knot that takes a few minutes to untie and be able to retie. The source, the target, and the action executed have the same linguistic root, not just once but three times.
The build instructions for the compiler, as of May 25th, 2020, states the converse, which is easier to understand but merely anecdotal, not getting at the cruz of the reason three stages are important.
If the comparison of stage2 and stage3 fails, this normally indicates that the stage2 compiler has compiled GCC incorrectly, and is therefore a potentially serious bug which you should investigate and report.
If we consider C/C++ development from a reliability assessment, test-first, eXtreme Programming, 6-Sigma, or Total Quality Management perspective, what component in a C/C++ development environment has to be more reliable than the compiler? Not many. And even the three stage bootstrapping of a compiler that the GNU compiler package has been using since early days is a reasonable but not an exhaustive test. That's why there are additional tests in the package.
From a continuous integration point of view, the entire body of software under development by those that are about to use the new compiler should be tested before and after a new compiler is compiled and deployed. That's the most convenient way to ensure new compiler didn't break the build.
Between the three reliability check points, most people are satisfied.
Ensuring the compiler compiles itself consistently
Other tests the compiler developers have put into their distribution
The developer or system administrators source code domain is not broken by the upgrade
On a mathematics side note, it is actually impossible to exhaustively test a compiler with the silicon and carbon available on planet earth. The bounds of recursion in C++ language abstractions (among other things) are infinite, so the silicon or time required places testing every permutation of source code cannot realistically exist. On the carbon side, no group of people can free up the requisite time to study the source sufficiently to guaranteed that some finite limit is not imposed in some way by the compiler source."
The three levels of checks, only one of which is the three stage bootstrap process, will likely suffice for most of us.
A further benefit of the three stage compile is that the new compiler is compiled with the new compiler which is presumably better either in terms of speed or resource consumption and possibly both.
Related
I just started to learn about compilers, and I wondered - is there a way to tell GCC (or any other compiler) to stop in the middle of the process, and give me a file with the current state (for example - a token tree)?
In general, yes!
When building a compiler, often one of your most important debugging tools is to see the current representation of the program, or even better, the states throughout compilation, so that when a transformation goes wrong -- i.e. a compiler bug -- it can be identified.
Dumping all the state of a compiler can be a lot however; Even just the intermediate representation for a large function can be tens-of-thousands of lines of plain-text. Then, there's also all the associated data structures: Control-flow graphs, dependency information, symbols etc.
See this question for some more detail on answers for LLVM and GCC.
I just realized that binary compilers convert source code to the binary of the destination platform. Kind of obvious... but if a compiler works such way, then how can the same compiler be used for different systems like x86, ARM, MIPS, etc?
Shouldn't they be supposed to "know" the machine-language of the hardware platform to be able to know how to build the binary? Does a compiler(like gcc) knows the machine language of every single platform that is supported?
How is that system possible, and how can a compiler be optimized for that many platforms at the same time?
Yes, they have to "know" the machine language for every single platform they support. This is a required to generate machine code. However, compilation is a multi-step process. Usually, the first steps of the compilation are common to most architectures.
Taken from wikipedia
Structure of a compiler
Compilers bridge source programs in high-level
languages with the underlying hardware.
A compiler requires
determining the correctness of the syntax of programs,
generating correct and efficient object code,
run-time organization, and
formatting output according to assembler and/or linker conventions.
A
compiler consists of three main parts: the frontend, the middle-end,
and the backend.
The front end
checks whether the program is correctly
written in terms of the programming language syntax and semantics.
Here legal and illegal programs are recognized. Errors are reported,
if any, in a useful way. Type checking is also performed by collecting
type information. The frontend then generates an intermediate
representation or IR of the source code for processing by the
middle-end.
The middle end
is where optimization takes place. Typical
transformations for optimization are removal of useless or unreachable
code, discovery and propagation of constant values, relocation of
computation to a less frequently executed place (e.g., out of a loop),
or specialization of computation based on the context. The middle-end
generates another IR for the following backend. Most optimization
efforts are focused on this part.
The back end
is responsible for translating the IR from the middle-end into assembly code. The target
instruction(s) are chosen for each IR instruction. Register allocation
assigns processor registers for the program variables where possible.
The backend utilizes the hardware by figuring out how to keep parallel
execution units busy, filling delay slots, and so on. Although most
algorithms for optimization are in NP, heuristic techniques are
well-developed.
More this article which describes the structure of a compiler and on this one which deals with Cross compilers.
The http://llvm.org/ project will answer all of your questions in this regard :)
In a nutshell, cross HW compilers emit "intermediate representation" of the code , which is HW agnostic and then its being customized via the native tool chain
Yes it is possible, it's called Cross Compiler. Compilers usually first they generate the object code which is not understanable by the current machine but it can be migrated to the destiny machine with another compiler. Next, object code is "compiled" again and linked with external libraries of the target machines.
TL;DR: Yes, the compilers knows the target code, but you can compile in another hardware.
I recommend you to read attached links for information.
Every platform has its own toolchain, toolchain includes gcc,gdb,ld,nm etc.
Let's take specific example of gcc as of now. GCC source code has many layers including architecture dependent and independent part. Architecture dependent part contains procedures to handle architecture specific things like their stack, function calls, floating point operations. We need to cross compile the gcc source code for a specific architecture like for ARM. You can see its steps here for reference:- http://www.ailis.de/~k/archives/19-arm-cross-compiling-howto.html#toolchain.
This architecture dependent part is responsible for handling machine language operations.
It is obvious that given any large codebase separate compilation of modules can significantly cut down compilation time. Still, I wonder if it worth to compile a production release in a single step, considering that the longer the code the more optimization can take place across. Is this presumption right?
The question is not language or tool specific but I’m particularly interested in C++ and GCC.
Yes it is. In fact, it's a compilation strategy that's used by almost any modern compiler out there.
You may want to look up IPO and LTO.
I've Googled and poked around the Go website, but I can't find an explanation for Go's extraordinary build times. Are they products of the language features (or lack thereof), a highly optimized compiler, or something else? I'm not trying to promote Go; I'm just curious.
Dependency analysis.
The Go FAQ used to contain the following sentence:
Go provides a model for software
construction that makes dependency
analysis easy and avoids much of the
overhead of C-style include files and
libraries.
While the phrase is not in the FAQ anymore, this topic is elaborated upon in the talk Go at Google, which compares the dependency analysis approach of C/C++ and Go.
That is the main reason for fast compilation. And this is by design.
I think it's not that Go compilers are fast, it's that other compilers are slow.
C and C++ compilers have to parse enormous amounts of headers - for example, compiling C++ "hello world" requires compiling 18k lines of code, which is almost half a megabyte of sources!
$ cpp hello.cpp | wc
18364 40513 433334
Java and C# compilers run in a VM, which means that before they can compile anything, the operating system has to load the whole VM, then they have to be JIT-compiled from bytecode to native code, all of which takes some time.
Speed of compilation depends on several factors.
Some languages are designed to be compiled fast. For example, Pascal was designed to be compiled using a single-pass compiler.
Compilers itself can be optimized too. For example, the Turbo Pascal compiler was written in hand-optimized assembler, which, combined with the language design, resulted in a really fast compiler working on 286-class hardware. I think that even now, modern Pascal compilers (e.g. FreePascal) are faster than Go compilers.
There are multiple reasons why the Go compiler is much faster than most C/C++ compilers:
Top reason: Most C/C++ compilers exhibit exceptionally bad designs (from compilation speed perspective). Also, from compilation speed perspective, some parts of the C/C++ ecosystem (such as editors in which programmers are writing their code) aren't designed with speed-of-compilation in mind.
Top reason: Fast compilation speed was a conscious choice in the Go compiler and also in the Go language
The Go compiler has a simpler optimizer than C/C++ compilers
Unlike C++, Go has no templates and no inline functions. This means that Go doesn't need to perform any template or function instantiation.
The Go compiler generates low-level assembly code sooner and the optimizer works on the assembly code, while in a typical C/C++ compiler the optimization passes work on an internal representation of the original source code. The extra overhead in the C/C++ compiler comes from the fact that the internal representation needs to be generated.
Final linking (5l/6l/8l) of a Go program can be slower than linking a C/C++ program, because the Go compiler is going through all of the used assembly code and maybe it is also doing other extra actions that C/C++ linkers aren't doing
Some C/C++ compilers (GCC) generate instructions in text form (to be passed to the assembler), while the Go compiler generates instructions in binary form. Extra work (but not much) needs to be done in order to transform the text into binary.
The Go compiler targets only a small number of CPU architectures, while the GCC compiler targets a large number of CPUs
Compilers which were designed with the goal of high compilation speed, such as Jikes, are fast. On a 2GHz CPU, Jikes can compile 20000+ lines of Java code per second (and the incremental mode of compilation is even more efficient).
Compilation efficiency was a major design goal:
Finally, it is intended to be fast: it should take at most a few seconds to build a large executable on a single computer. To meet these goals required addressing a number of linguistic issues: an expressive but lightweight type system; concurrency and garbage collection; rigid dependency specification; and so on. FAQ
The language FAQ is pretty interesting in regards to specific language features relating to parsing:
Second, the language has been designed to be easy to analyze and can be parsed without a symbol table.
While most of the above is true, there is one very important point that was not really mentionend: Dependency management.
Go only needs to include the packages that you are importing directly (as those already imported what they need). This is in stark contrast to C/C++, where every single file starts including x headers, which include y headers etc. Bottom line: Go's compiling takes linear time w.r.t to the number of imported packages, where C/C++ take exponential time.
A good test for the translation efficiency of a compiler is self-compilation: how long does it take a given compiler to compile itself? For C++ it takes a very long time (hours?). By comparison, a Pascal/Modula-2/Oberon compiler would compile itself in less than one second on a modern machine [1].
Go has been inspired by these languages, but some of the main reasons for this efficiency include:
A clearly defined syntax that is mathematically sound, for efficient scanning and parsing.
A type-safe and statically-compiled language that uses separate compilation with dependency and type checking across module boundaries, to avoid unnecessary re-reading of header files and re-compiling of other modules - as opposed to independent compilation like in C/C++ where no such cross-module checks are performed by the compiler (hence the need to re-read all those header files over and over again, even for a simple one-line "hello world" program).
An efficient compiler implementation (e.g. single-pass, recursive-descent top-down parsing) - which of course is greatly helped by points 1 and 2 above.
These principles have already been known and fully implemented in the 1970s and 1980s in languages like Mesa, Ada, Modula-2/Oberon and several others, and are only now (in the 2010s) finding their way into modern languages like Go (Google), Swift (Apple), C# (Microsoft) and several others.
Let's hope that this will soon be the norm and not the exception. To get there, two things need to happen:
First, software platform providers such as Google, Microsoft and Apple should start by encouraging application developers to use the new compilation methodology, while enabling them to re-use their existing code base. This is what Apple is now trying to do with the Swift programming language, which can co-exist with Objective-C (since it uses the same runtime environment).
Second, the underlying software platforms themselves should eventually be re-written over time using these principles, while simultaneously redesigning the module hierarchy in the process to make them less monolithic. This is of course a mammoth task and may well take the better part of a decade (if they are courageous enough to actually do it - which I am not at all sure in the case of Google).
In any case, it's the platform that drives language adoption, and not the other way around.
References:
[1] http://www.inf.ethz.ch/personal/wirth/ProjectOberon/PO.System.pdf, page 6: "The compiler compiles itself in about 3 seconds". This quote is for a low cost Xilinx Spartan-3 FPGA development board running at a clock frequency of 25 MHz and featuring 1 MByte of main memory. From this one can easily extrapolate to "less than 1 second" for a modern processor running at a clock frequency well above 1 GHz and several GBytes of main memory (i.e. several orders of magnitude more powerful than the Xilinx Spartan-3 FPGA board), even when taking I/O speeds into account. Already back in 1990 when Oberon was run on a 25MHz NS32X32 processor with 2-4 MBytes of main memory, the compiler compiled itself in just a few seconds. The notion of actually waiting for the compiler to finish a compilation cycle was completely unknown to Oberon programmers even back then. For typical programs, it always took more time to remove the finger from the mouse button that triggered the compile command than to wait for the compiler to complete the compilation just triggered. It was truly instant gratification, with near-zero wait times. And the quality of the produced code, even though not always completely on par with the best compilers available back then, was remarkably good for most tasks and quite acceptable in general.
Go was designed to be fast, and it shows.
Dependency Management: no header file, you just need to look at the packages that are directly imported (no need to worry about what they import) thus you have linear dependencies.
Grammar: the grammar of the language is simple, thus easily parsed. Although the number of features is reduced, thus the compiler code itself is tight (few paths).
No overload allowed: you see a symbol, you know which method it refers to.
It's trivially possible to compile Go in parallel because each package can be compiled independently.
Note that Go isn't the only language with such features (modules are the norm in modern languages), but they did it well.
Quoting from the book "The Go Programming Language" by Alan Donovan and Brian Kernighan:
Go compilation is notably faster than most other compiled languages, even when building from scratch. There are three main reasons for the compiler’s speed. First, all imports must be explicitly listed at the beginning of each source file, so the compiler does not have to read and process an entire file to determine its dependencies. Second, the dependencies of a package form a directed acyclic graph, and because there are no cycles, packages can be compiled separately and perhaps in parallel. Finally, the object file for a compiled Go package records export information not just for the package itself, but for its dependencies too. When compiling a package, the compiler must read one object file for each import but need not look beyond these files.
The basic idea of compilation is actually very simple. A recursive-descent parser, in principle, can run at I/O bound speed. Code generation is basically a very simple process. A symbol table and basic type system is not something that requires a lot of computation.
However, it is not hard to slow down a compiler.
If there is a preprocessor phase, with multi-level include directives, macro definitions, and conditional compilation, as useful as those things are, it is not hard to load it down. (For one example, I'm thinking of the Windows and MFC header files.) That is why precompiled headers are necessary.
In terms of optimizing the generated code, there is no limit to how much processing can be added to that phase.
Simply ( in my own words ), because the syntax is very easy ( to analyze and to parse )
For instance, no type inheritance means, not problematic analysis to find out if the new type follows the rules imposed by the base type.
For instance in this code example: "interfaces" the compiler doesn't go and check if the intended type implement the given interface while analyzing that type. Only until it's used ( and IF it is used ) the check is performed.
Other example, the compiler tells you if you're declaring a variable and not using it ( or if you are supposed to hold a return value and you're not )
The following doesn't compile:
package main
func main() {
var a int
a = 0
}
notused.go:3: a declared and not used
This kinds of enforcements and principles make the resulting code safer, and the compiler doesn't have to perform extra validations that the programmer can do.
At large all these details make a language easier to parse which result in fast compilations.
Again, in my own words.
Go imports dependencies once for all files, so the import time doesn't increase exponentially with project size.
Simpler linguistics means interpreting them takes less computing.
What else?
I was thinking more about the programming language i am designing. and i was wondering, what are ways i could minimize its compile time?
Your main problem today is I/O. Your CPU is many times faster than main memory and memory is about 1000 times faster than accessing the hard disk.
So unless you do extensive optimizations to the source code, the CPU will spend most of the time waiting for data to be read or written.
Try these rules:
Design your compiler to work in several, independent steps. The goal is to be able to run each step in a different thread so you can utilize multi-core CPUs. It will also help to parallelize the whole compile process (i.e. compile more than one file at the same time)
It will also allow you to load many source files in advance and preprocess them so the actual compile step can work faster.
Try to allow to compile files independently. For example, create a "missing symbol pool" for the project. Missing symbols should not cause compile failures as such. If you find a missing symbol somewhere, remove it from the pool. When all files have been compiled, check that the pool is empty.
Create a cache with important information. For example: File X uses symbols from file Y. This way, you can skip compiling file Z (which doesn't reference anything in Y) when Y changes. If you want to go one step further, put all symbols which are defined anywhere in a pool. If a file changes in such a way that symbols are added/removed, you will know immediately which files are affected (without even opening them).
Compile in the background. Start a compiler process which checks the project directory for changes and compile them as soon as the user saves the file. This way, you will only have to compile a few files each time instead of everything. In the long run, you will compile much more but for the user, turnover times will be much shorter (= time user has to wait until she can run the compiled result after a change).
Use a "Just in time" compiler (i.e. compile a file when it is used, for example in an import statement). Projects are then distributed in source form and compiled when run for the first time. Python does this. To make this perform, you can precompile the library during the installation of your compiler.
Don't use header files. Keep all information in a single place and generate header files from the source if you have to. Maybe keep the header files just in memory and never save them to disk.
what are ways i could minimize its compile time?
No compilation (interpreted language)
Delayed (just in time) compilation
Incremental compilation
Precompiled header files
I've implemented a compiler myself, and ended up having to look at this once people started batch feeding it hundreds of source files. I was quite suprised what I found out.
It turns out that the most important thing you can optimize is not your grammar. It's not your lexical analyzer or your parser either. Instead, the most important thing in terms of speed is the code that reads in your source files from disk. I/O's to disk are slow. Really slow. You can pretty much measure your compiler's speed by the number of disk I/Os it performs.
So it turns out that the absolute best thing you can do to speed up a compiler is to read the entire file into memory in one big I/O, do all your lexing, parsing, etc. from RAM, and then write out the result to disk in one big I/O.
I talked with one of the head guys maintaining Gnat (GCC's Ada compiler) about this, and he told me that he actually used to put everything he could onto RAM disks so that even his file I/O was really just RAM reads and writes.
In most languages (pretty well everything other than C++), compiling individual compilation units is quite fast.
Binding/linking is often what's slow - the linker has to reference the whole program rather than just a single unit.
C++ suffers as - unless you use the pImpl idiom - it requires the implementation details of every object and all inline functions to compile client code.
Java (source to bytecode) suffers because the grammar doesn't differentiate objects and classes - you have to load the Foo class to see if Foo.Bar.Baz is the Baz field of object referenced by the Bar static field of the Foo class, or a static field of the Foo.Bar class. You can make the change in the source of the Foo class between the two, and not change the source of the client code, but still have to recompile the client code, as the bytecode differentiates between the two forms even though the syntax doesn't. AFAIK Python bytecode doesn't differentiate between the two - modules are true members of their parents.
C++ and C suffer if you include more headers than are required, as the preprocessor has to process each header many times, and the compiler compile them. Minimizing header size and complexity helps, suggesting better modularity would improve compilation time. It's not always possible to cache header compilation, as what definitions are present when the header is preprocessed can alter its semantics, and even syntax.
C suffers if you use the preprocessor a lot, but the actual compilation is fast; much of C code uses typedef struct _X* X_ptr to hide implementation better than C++ does - a C header can easily consist of typedefs and function declarations, giving better encapsulation.
So I'd suggest making your language hide implementation details from client code, and if you are an OO language with both instance members and namespaces, make the syntax for accessing the two unambiguous. Allow true modules, so client code only has to be aware of the interface rather than implementation details. Don't allow preprocessor macros or other variation mechanism to alter the semantics of referenced modules.
Here are some performance tricks that we've learned by measuring compilation speed and what affects it:
Write a two-pass compiler: characters to IR, IR to code. (It's easier to write a three-pass compiler that goes characters -> AST -> IR -> code, but it's not as fast.)
As a corollary, don't have an optimizer; it's hard to write a fast optimizer.
Consider generating bytecode instead of native machine code. The virtual machine for Lua is a good model.
Try a linear-scan register allocator or the simple register allocator that Fraser and Hanson used in lcc.
In a simple compiler, lexical analysis is often the greatest performance bottleneck. If you are writing C or C++ code, use re2c. If you're using another language (which you will find much more pleasant), read the paper aboug re2c and apply the lessons learned.
Generate code using maximal munch, or possibly iburg.
Surprisingly, the GNU assembler is a bottleneck in many compilers. If you can generate binary directly, do so. Or check out the New Jersey Machine-Code Toolkit.
As noted above, design your language to avoid anything like #include. Either use no interface files or precompile your interface files. This tactic dramatically reduces the burdern on the lexer, which as I said is often the biggest bottleneck.
Here's a shot..
Use incremental compilation if your toolchain supports it.
(make, visual studio, etc).
For example, in GCC/make, if you have many files to compile, but only make changes in one file, then only that one file is compiled.
Eiffel had an idea of different states of frozen, and recompiling didn't necessarily mean that the whole class was recompiled.
How much can you break up the compliable modules, and how much do you care to keep track of them?
Make the grammar simple and unambiguous, and therefore quick and easy to parse.
Place strong restrictions on file inclusion.
Allow compilation without full information whenever possible (eg. predeclaration in C and C++).
One-pass compilation, if possible.
One thing surprisingly missing in answers so far: make you you're doing a context free grammar, etc. Have a good hard look at languages designed by Wirth such as Pascal & Modula-2. You don't have to reimplement Pascal, but the grammar design is custom made for fast compiling. Then see if you can find any old articles about the tricks Anders pulled implementing Turbo Pascal. Hint: table driven.
it depends on what language/platform you're programming for. for .NET development, minimise the number of projects that you have in your solution.
In the old days you could get dramatic speedups by setting up a RAM drive and compiling there. Don't know if this still holds true, though.
In C++ you could use distributed compilation with tools like Incredibuild
A simple one: make sure the compiler can natively take advantage of multi-core CPUs.
Make sure that everything can be compiled the fist time you try to compile it. E.g. ban forward references.
Use a context free grammar so that you can find the correct parse tree without a symbol table.
Make sure that the semantics can be deduced from the syntax so you can construct the correct AST directly rather than by mucking with a parse tree and symbol table.
How serious a compiler is this?
Unless the syntax is pretty convoluted, the parser should be able to run no more than 10-100 times slower than just indexing through the input file characters.
Similarly, code generation should be limited by output formatting.
You shouldn't be hitting any performance issues unless you're doing a big, serious compiler, capable of handling mega-line apps with lots of header files.
Then you need to worry about precompiled headers, optimization passes, and linking.
I haven't seen much work done for minimizing the compile time. But some ideas do come to mind:
Keep the grammar simple. Convoluted grammar will increase your compile time.
Try making use of parallelism, either using multicore GPU or CPU.
Benchmark a modern compiler and see what are the bottlenecks and what you can do in you compiler/language to avoid them.
Unless you are writing a highly specialized language, compile time is not really an issue..
Make a build system that doesn't suck!
There's a huge amount of programs out there with maybe 3 source files that take under a second to compile, but before you get that far you'd have to sit through an automake script that takes about 2 minutes checking things like the size of an int. And if you go to compile something else a minute later, it makes you sit through almost exactly the same set of tests.
So unless your compiler is doing awful things to the user like changing the size of its ints or changing basic function implementations between runs, just dump that info out to a file and let them get it in a second instead of 2 minutes.