Direct Clojure to C Compiler - Based on ClojureScript
github.com
github.com
I hope these developments eventually turn into a proper Lisp that you can interface with native C code efficiently.
Racket is pretty cool too.
Clojure is a Lisp-1, and provides better data structures as Common Lisp as far as I am aware.
But the JVM benefit is a big one indeed.
I don't fully grasp the advantages of being a Lisp-1 or Lisp-2 :)
It has to do with variable scoping. Lisp-1 only accepts lexical scoping, while Lisp-2 also allows for dynamic scoping.
No.
Lisp-N has to do with the number of name spaces in the language. Lisp-1s only have ONE environment; the variables range over all values of the language, integers, functions, vectors, symbols, strings. In Lisp-N, there are N namespaces for each "kind" of value.
Common Lisp is called a "Lisp-2" because it separates functions from other values. (it's closer to Lisp-5 or even Lisp-7, forgot which, because it allows that many kinds of "names" without collission.
Also above you said Clojure "probably" has better data structures than Common Lisp. That is unsubstantiated.
I'm not much of a common lisp programmer (mostly sticking with scheme/racket and Clojure), but I don't think they've been ported to Common Lisp (yet), so the claim that Clojure has better data structures than Common Lisp, while somewhat a matter of preference, isn't entirely unsubstantiated.
The language provides a wealth of tools out of the box, but it's the job of the programmer to choose more appropriate tools for the problems at hand.
The following is the Common Lisp specification. 12+ implementations, half of them industrial strength, more than half commercial vendors, and everyone of them has to adhere to this spec:
http://www.franz.com/support/documentation/8.2/ansicl/ansicl...
If you mean can users extend the core CL data-types, no, but you have a wealth of tools to do that yourself; use generic functions to implement whatever interface you wish, then provide for specific implementations.
That's the problem. With Clojure you don't have to invent interfaces and then convince other libraries to use them. All the data structures are built upon well considered language level protocols that anyone can implement preventing pointless API proliferation.
Personally, I slightly prefer Clojure over SBCL.
It is my understanding that Common Lisp lacks the vector and hash maps that Clojure has.
Sorry if I got it wrong. I am more a ML guy than Lisp.
From the documentation I have not seen the simplified syntax Clojure uses for vectors, hashes and sets.
I imagine that the syntax is Clojure specific.
Also, Clojure supports (optional) dynamically scoped variables.
I guess it also helps to work with a dialect with more momentum. E.g. its easier to find support, on- and offline.
Since I haven't really used Closure or any other Lisp for more than a tutorial, I might be very wrong, though.
Here is one example, http://www.atego.com/products/aonix-perc/
If you intend to distribute your software (as opposed to running on your own servers), it would require all the customers to have a fancy JVM. Or buying an expensive license to be able to distribute the runtime with your software.
Why is it a bad thing that someone was willing to pay money to make Java fast. Do you want to say that there haven't been billions of dollars in both money and man-hours thrown at trying to make C/C++ fast? There's no free performance.
I guess there's someone who wants to pay for that.
But I don't think it's money well spent. The Java bytecode is not designed for or suited to fast execution and it's a bad intermediate representation for computer programs to be compiled into native code. The Java byte code was designed to be easy to interpret and was designed at a time when a memory access was faster to execute than an ALU instruction (on cheap h/w where Java was originally intended to be run on). Those days have passed and we should move on to better intermediate representations for computer programs. Like LLVM IR.
VMkit is a nice effort, though. I hope it will some day power fancy new languages that have dynamic features which are not well suited for AOT compilation.
These are native code compilers without any need of extra runtime exactly like C.
Just because most people only know Oracle(Sun)'s JVM, it does not mean it is the only way to execute Java code.
So maybe you mean static compilation, but then, why is it better for the stuff you're doing ?
By native code I mean binaries emitted by my compiler in a format that my operating system can link and load. I usually write the code in C with some CPU-specific assembly intrinsics for the critical stuff.
I tend to write computer graphics and physics simulation stuff which has to be quite fast. A lot of stuff I deal with is moving blobs of binary data from buffer to another (disk, memory, dma, gpu). Or computing a SIMD fused multiply-and-add for a few hundred megabytes of floating point data. Or invert and transpose a hundred thousand 4x4 matrices. Everything the JVM does is acting against me, so better just write native.
Sure there are games and physics and whatnot written with Java and other systems, but they are more commonly "low perf" stuff. 2d games and that kind of stuff. And even then they suffer from JIT & GC pauses and other undesirable effects. It always ruins my day when in the middle of a Minecraft session the GC kicks in while running away from a Creeper.
The JVM is very fast for these things. There remaining delta is the result of more investment into optimizations in GCC/LLVM than any limitation of the JVM model itself.
GC, allocation, thread management, OS interfacing and compilation (JIT or AOT) together make up a VM. Removing the compilation part doesn't make the rest of your VM requirements disappear.
Having used a number of various VMs in the Common Lisp world (yes, including one implementation that went through C) I value the JVM greatly. It is an impressive engineering effort.
Also, I wrote code like yours (hand-written x86-64 SIMD assembly). I then used it from Clojure through JNA and was quite happy with the results.
Yes, you might need to free some heap memory with C and having malloc/free cause GC-like performance. That's why I have zero mallocs in the fast path. The bad part in GC is the unpredictability, which makes it unsuitable for games, simulation and multimedia stuff. But for most allocs I can get away with using the stack, which is essentially free (a possibility of a page fault exists).
> Also, I wrote code like yours (hand-written x86-64 SIMD assembly). I then used it from Clojure through JNA and was quite happy with the results.
Yes that works quite well as long as the foreign function is big enough.
What I have is a bunch of code written with C intrinsics, mostly small functions which I use a handful of for a big bunch of data. What I want is that inner loop to be efficient yet readable.
With C and intrinsics I get interprocedural optimization between the small functions. Everything gets inlined and all the values are stored in registers. There are a few hundred SSE math instructions without a single memory operation in between. I get the compiler to do register allocation for instruction scheduling for me, which it is great at (and I suck in) and leaves me with the instruction selection which it is not so great at.
Now had this been written with any higher level language, or even C across translation units (without link time optimization), my resulting code would be a lot worse. In particular, live values get spilled out of registers to memory when theres a foreign function call (as per abi requirements).
The non-fast path of my project could very well be written in any language as long as the beef would be written in C or similar. I would have to avoid allocating new heap objects to avoid GC unpredicatbility.
It'd be nice if somebody made a new systems language to succeed C or C++. Rust is looking less likely these days. Maybe Clay or Deca?
It's like the inverse of golang. golang is unimpressive, and totally impractical for systems programming, but is nice to use for general purpose programming.
Rust is impressive and could'ish be used for systems programming (I'm not sure how much uphill fighting is involved with the current memory management model, it seems ARC is the default which makes me intensely uncomfortable about its prospects for 'hard' systems programming) but it's not very pleasant at all. The syntax and semantics make me nauseous.
Rust can be fixed, golang cannot. Unlikely though.
I'm not sure it's more realistic to make a practical implementation of region-based memory management than it is to ameliorate the pains of day-to-day systems programming in C.
There is a lot of low-hanging fruit when it comes to systems programming if you're allowed to make a language from scratch and they've not really capitalized on much of that due to ambition.
For me, because I don't want to install the JVM, or force users of my stuff to install the JVM. I also don't care about JVM libs.
>What do you even mean by native code ? The JVM does produce native code, it just does it at runtime (JIT compilation).
I, for one, mean non-JIT, no virtual machine needed, native code.
>So maybe you mean static compilation, but then, why is it better for the stuff you're doing ?
Less startup overhead. Small binaries. Easily redistributable. No stuff I don't need.
Are you forced to use as environment like:
typedef struct environment {
struct environment *up;
int num_bindings;
value_t *bindings [0];
} environment_t;
Say you have an outer lambda and an inner lambda. All variables (either arguments or local variables introduced by "let") defined in the outer lambda and used in the inner lambda are called the "free variables" of the inner lambda and the "closed over variables" of the outer lambda. Of the closed over variables of the outer lambda, all the ones that are assigned-to in the inner lambda are "assigned to variables." You can perform this classification in one pass before code generation.
Once you have annotated each lexical variable with its "closed over" and "assigned to" status, you can generate flat C functions in one code generation pass. The idea is to generate each inner lambda as a C function that accepts a hidden "environment vector" that contains the closed-over variables in the outer lambda. This environment vector is indexed simply by an integer index. Just handle the following AST constructs as follows:
LET: if the lexical variable introduced by the LET form is closed-over and assigned-to, it must be demoted to a box because the inner lambda can't modify the outer lambda's stack frame. Whereas you can generate a regular lexical variable directly as a C local variable, you have to generate a closed-over + assigned-to variable as a C variable that points to a single heap-allocated box that references a Lisp value.
VARIABLE-REF: for every reference to a variable, you have to look at it's status. If the variable is defined in the current lambda and not assigned-to, you can just emit a use of the C variable directly. If it is defined in the current lambda and assigned-to, you have to emit a load of the value from its box, a pointer to which is in a C variable in the current function. If the variable is defined in an outer lambda (it's a free variable of the current lambda), but not assigned-to, you have to emit the reference as a load (with a known constant index) from the environment vector. If it's a free variable and assigned-to, you have to load a reference to a box from the environment vector, then load the value from the box.
LAMBDA: assign each free variable of the lambda an index starting at 0 (which you will use when emitting references to free variables in the body of the lambda). Generate the LAMBDA expression as the creation of an object with two slots: a pointer to the C function of the inner lambda, and a pointer to an environment vector. Emit code to copy each free variable referenced in the inner lambda into the environment vector. Remember you might have multiple levels of nested lambdas, so follow the rules for VARIABLE-REF above when emitting each copy.
Then, just structure your calling convention so you can FUNCALL lambda objects and pas the environment vector as a hidden first argument.
Note that this requires a bit more environment book-keeping in your compiler than you might otherwise have. You really want each inner lambda to have a complete environment, including free variables. This is so you can keep track of which variable has which index in the environment vector. Say you have:
(defun foo()
(let ((x 0) (y 1) (z 2))
(labels ((bar () (+ x y))
(baz () (- z x)))
...)))
In practice this generates very good code, because most lambdas simply don't have very many free variables (at least so long as you don't naively generate LET forms as nested lambdas).
(define x 2)
(define y (lambda (z) (+ x z))
(set! x 3)
(define x (make-ref 2))
(define y (lambda (z) (+ (read-ref x) z))
(set-ref! x 3)
(let ((x 1) (y 2))
(lambda (z) (+ x z))
However, keep in mind that what you usually not think of as free variables are free variables. For example if you have this:
(let ((y 4))
(map (lambda (x) (factorial (+ x y))) xs))
See Andrew Appel's "Compiling with Continuations", for example.
(let [x 1]
(defn make-adder [y]
(fn [] (+ x y)))
(defn make-multiplier [z]
(fn [] (* x z)))
(defn mutate! [new-x]
(set! x new-x)))
(make-adder 2)
(make-multiplier 2)
(mutate! 3)
(lambda (a) (lambda (b) (lambda (c) (lambda (d) (lambda (e) a)))))http://shootout.alioth.debian.org/u64/benchmark.php?test=all...
"Don't confuse differences in default memory allocation with differences in Memory-used when the task requires programs to allocate more than the default memory."
Look at memory use for reverse-complement, k-nucleotide, regex-dna, binary-trees, mandelbrot.
http://research.microsoft.com/apps/pubs/default.aspx?id=7985...
I would be able to leave with Clojurescript limitations compared to Clojure if it provides smaller jar files and better performance of compiled code. That would make it really usable on constrained targets like Android.
Contributors are always welcome ;-)
I'm curious what the end result would look like! :-)
The C code will not be optimized C (like a seasoned C developer would write). Java is compiled to byte code which is compiled to machine language. This ugly, unoptimized, generated C is compiled into machine language too. The performance (both memory and CPU usage) of the JVM product will be far superior through.
Don't think that you will be writing for embedded devices or device drivers with something like this. it will be a mess. Use C for things that should to be done in C. For Desktop apps, Web apps, or services use Closure ETC.
I don't like seeing a square peg rammed into a round hole. It does not work well so don't get too exited lisp programmers. This is an interesting hobby - that is about it.
How do you know that the C code, when passed through an optimizing compiler, will not be able to compete with the JVM? Have you done these tests? The author already mentioned on this page that the goal is to get it working, and then focus on performance. As far as I can tell, he is a "seasoned C developer" and should be able to construct the generated C so that it compiles efficiently.
Without more than mere pessimistic speculation, your failure to contribute any sort of primary or objective information does little more than to make you appear curiously angry at a project in which you have no interest or affiliation.
EDIT: Just read through your comment history. A lot of your posts are written in this sort of negative tone. Why do you do that? If you would provide some links or alternative viewpoints, substantiated with a paper or even a blog post, that would be a lot more insightful.
Why do this? this should compile to native machine language directly if anything. Would you transform it to C first so you could edit the C? Then what if you want to make a big update using the Closure source? it will overwrite your changes.
This approach is not practical, perhaps I am failing to understand any logic as to why you would go with this approach. Portability (between processor architectures) is all I can think of but you will never achieve competitive performance if this is the case.
Good C coders write their code differently against different processors and platforms because all machines have different capabilities and resources (strength and weaknesses). The whole point these days of writing something in C to achieve the second highest performance (only behind pure assembly language) in both processor gpu/cpu/other co-processors and at the same time using as little memory as possible (both ram and NV storage).
Although I can understand your point in the second paragraph. Indeed, C is a language that is nowadays mostly suited for performance-oriented application. The reason the author translates Clojure code into C, and then into machine code is that this is vastly easier than going straight to native code. As you say, there are so many platforms with different sets of instructions that it would be almost pointless to write an optimized compiler directly from Clojure code to all these platforms, particularly since Clojure is still a somewhat obscure language.
The value in doing this is that Clojure promotes good programming practices. In turn, this means that someone who has little experience with embedded systems or hand-optimizing assembly can write better performing code in Clojure -> C -> assembly than if they tried to use C without any experience. Sure, it won't be as fast as if they were an experienced assembly guru, but the difference will only be a factor of 1-2 -- the algorithm is much more important than the compilation, and this is where Clojure shines.
One other use is when a project is not performance-oriented, but development-oriented. A fast development cycle is in a lot of situations much more important than the speed at which the code runs. As Clojure is currently limited to the JVM (and Javascript maybe??), extending this support to C now extends the domain of Clojure to almost anything.
These languages are not comparable equivalents. Their specialties are completely opposite. To make their output equivalent, you would have to construct an AI system more advanced than anything that exists today.
Umm......
Speaking of IOS - This IS an area where this may be practical, but that is only because of politics (Apple's tyrannical restrictions). But there are already closure compilers for IOS.
Ricoh printers have a JVM builtin, http://ricoh-ridp.com/sdkj
Simple math.
And I can tell you that a well known mobile company originally from UK, available in most European countries, makes use of Java for Smartcards on their SIM cards.
You made your math wrong. Nowadays, specially if we put outsourcing in the equation, hiring Java developers is way cheaper than hiring C developers, specially since many universities don't teach C any longer.
There is very little about C that makes this inherently slow, and almost all of the stuff one has to do to make it fast has to be done when targeting machine code as well.
On the other hand the C compiler does lots of things very well that would otherwise have to be coded by hand, like register allocation, interfacing with existing code, and, yes, portability.
Closure is awesome and has it's place, C is the industry standard for performance and also has it's place. The lines will never be crossed between these two languages.
You are trying to fit a square peg in a round hole. If you improve your skills from this project - great, but please don't try to mislead anyone that this is a viable replacement for C (be up front about this).
A language from an entirely different paradigm (Functional language, Garbage collection, tons of abstractions and a huge API) cannot ever be a replacement for or even compete on the same playing field C. We are talking apples to oranges here.
This approach is not practical, perhaps I am failing to understand any logic as to why you would go with this approach. Portability (between processor architectures) is all I can think of but you will never achieve high performance if this is the case.
C coders write their code differently against different processors because all machines have different capabilities and resources (strength and weaknesses).
[1] http://dynamo.iro.umontreal.ca/~gambit/wiki/index.php/Main_P...
see also:
http://www.iro.umontreal.ca/~boucherd/mslug/meetings/2004102...
http://www.iro.umontreal.ca/~boucherd/mslug/meetings/2004102...