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# Writing the Cyclone Scheme Compiler (Revision 1)
###### by [Justin Ethier](https://github.com/justinethier)
This document covers some of the background on how Cyclone was written, including aspects of the compiler and runtime system. This is a revision of the [original document](Writing-the-Cyclone-Scheme-Compiler.md), written over a year ago when the compiler was self hosting but before the new garbage collector was written. This document
Before we get started, I want to give a big **Thank You** to everyone that has contributed to the Scheme community. Cyclone is based on the latest revision of the Scheme language, developed by the large community, and wherever possible existing code from the community was reused or repurposed for this project instead of starting from scratch.
At the end of this document is a list of online resources that were the most helpful and influential. Without quality Scheme resources like these it would not have been possible to write Cyclone.
In addition, developing [Husk Scheme](http://justinethier.github.io/husk-scheme) helped me gather much of the knowledge that would later be used to build Cyclone. In fact, the primary motivation in building Cyclone was to go a step further and understand how to build a full, free-standing Scheme system. At this point Cyclone has eclipsed the speed and functionality of Husk and it is not clear if Husk will receive much more than bug fixes at this point. Maybe if there is greater interest from the community some of this can be ported back to that project.
## Table of Contents
- [Overview](#overview)
- [Source-to-Source Transformations](#source-to-source-transformations)
- [C Code Generation](#c-code-generation)
- [Garbage Collector](#garbage-collector)
- [C Runtime](#c-runtime)
- [Data Types](#data-types)
- [Interpreter](#interpreter)
- [Macros](#macros)
- [Scheme Standards](#scheme-standards)
- [Future](#future)
- [Conclusion](#conclusion)
- [References](#references)
## Overview
Cyclone has a similar architecture to other modern compilers:
<img src="images/compiler.png" alt="flowchart of cyclone compiler">
First, an input file containing Scheme code is received on the command line and loaded into an abstract syntax tree (AST) by Cyclone's parser. From there a series of source-to-source transformations are performed on the AST to expand macros, perform optimizations, and make the code easier to compile to C. These intermediate representations (IR) can be printed out in a readable format to aid debugging. The final AST is then output as a `.c` file and the C compiler is invoked to create the final executable or object file.
The code is represented internally as an AST of regular Scheme objects. Since Scheme represents both code and data using [S-expressions](https://en.wikipedia.org/wiki/S-expression), our compiler does not (in general) have to use custom abstract data types to store the code as would be the case with many other languages.
## Source-to-Source Transformations
### Overview
My primary inspiration for Cyclone was Marc Feeley's [The 90 minute Scheme to C compiler](http://churchturing.org/y/90-min-scc.pdf) (also [video](https://www.youtube.com/watch?v=TxOM9Y5YrCs) and [code](https://github.com/justinethier/nugget/tree/master/90-min-scc)). Over the course of 90 minutes, Feeley demonstrates how to compile Scheme to C code using source-to-source transformations, including closure and continuation-passing-style (CPS) conversions.
As outlined in the presentation, some of the difficulties in compiling to C are:
> Scheme has, and C does not have
>
> - tail-calls a.k.a. tail-recursion optimization
> - first-class continuations
> - closures of indefinite extent
> - automatic memory management i.e. garbage collection (GC)
>
> Implications
>
> - cannot translate (all) Scheme calls into C calls
> - have to implement continuations
> - have to implement closures
> - have to organize things to allow GC
>
> The rest is easy!
To overcome these difficulties a series of source-to-source transformations are used to remove powerful features not provided by C, add constructs required by the C code, and restructure/relabel the code in preparation for generating C. The final code may be compiled direcly to C. Cyclone also includes many other intermediate transformations, including:
- Macro expansion
- Processing of globals
- [Alpha conversion](https://wiki.haskell.org/Alpha_conversion)
- [CPS conversion](https://en.wikipedia.org/wiki/Continuation-passing_style)
- [Closure conversion](http://matt.might.net/articles/closure-conversion/)
The 90-minute compiler ultimately compiles the code down to a single function and uses jumps to support continuations. This is a bit too limiting for a production compiler, so that part was not used.
### CPS Conversion
TODO: what is CPS, why we need it (cheney on mta requires it)
### CPS Optimizations
TODO: CPS conversion generates too much code, need to optimize it to make the compiler practical
types of optimizations - inlining is the key (explain with examples), what else?
ideas from chicken - analysis pass, analysis DB
A custom AST is used to represent some object during CPS optimizations though
TODO:
Andrew Appel used a similar runtime for [Standard ML of New Jersey](http://www.smlnj.org/) which is referenced by Baker's paper. Appel's book [Compiling with Continuations](http://www.amazon.com/Compiling-Continuations-Andrew-W-Appel/dp/052103311X) includes a section on how to implement compiler optimizations - many of which could be applied to Cyclone.
## C Code Generation
The compiler's code generation phase takes a single pass over the transformed Scheme code and outputs C code to the current output port (usually a `.c` file).
During this phase C code is sometimes returned for later use instead of being output directly. For example, when compiling a vector literal or a series of function arguments. In this case, the code is returned as a list of strings that separates variable declarations from C code in the "body" of the generated function.
The C code is carefully generated so that a Scheme library (`.sld` file) is compiled into a C module. Functions and variables exported from the library become C globals in the generated code.
## Garbage Collector
### Background: Cheney on the MTA
A runtime based on Henry Baker's paper [CONS Should Not CONS Its Arguments, Part II: Cheney on the M.T.A.](http://www.pipeline.com/~hbaker1/CheneyMTA.html) was used as it allows for fast code that meets all of the fundamental requirements for a Scheme runtime: tail calls, garbage collection, and continuations.
Baker explains how it works:
> We propose to compile Scheme by converting it into continuation-passing style (CPS), and then compile the resulting lambda expressions into individual C functions. Arguments are passed as normal C arguments, and function calls are normal C calls. Continuation closures and closure environments are passed as extra C arguments. Such a Scheme never executes a C return, so the stack will grow and grow ... eventually, the C "stack" will overflow the space assigned to it, and we must perform garbage collection.
Cheney on the M.T.A. uses a copying garbage collector. By using static roots and the current continuation closure, the GC is able to copy objects from the stack to a pre-allocated heap without having to know the format of C stack frames. To quote Baker:
> the entire C "stack" is effectively the youngest generation in a generational garbage collector!
After GC is finished, the C stack pointer is reset using [`longjmp`](http://man7.org/linux/man-pages/man3/longjmp.3.html) and the GC calls its continuation.
Here is a snippet demonstrating how C functions may be written using Baker's approach:
object Cyc_make_vector(object cont, object len, object fill) {
object v = NULL;
int i;
Cyc_check_int(len);
// Memory for vector can be allocated directly on the stack
v = alloca(sizeof(vector_type));
// Populate vector object
((vector)v)->tag = vector_tag;
...
// Check if GC is needed, then call into continuation with the new vector
return_closcall1(cont, v);
}
[CHICKEN](http://www.call-cc.org/) was the first Scheme compiler to use Baker's approach.
### Cyclone's Hybrid Collector
Cyclone uses generational garbage collection (GC) to automatically free allocated memory using two types of collection. In practice, most allocations consist of short-lived objects such as temporary variables. Minor GC is done frequently to clean up most of these short-lived objects. Some objects will survive this collection because they are still referenced in memory. A major collection runs less often to free longer-lived objects that are no longer being used by the application.
Cheney on the MTA, is used to implement the first generation of our garbage collector. Objects are allocated directly on the stack using `alloca` so allocations are very fast, do not cause fragmentation, and do not require a special pass to free unused objects.
Baker's technique uses a copying collector for both the minor and major generations of collection. One of the drawbacks of using a copying collector for major GC is that it relocates all the live objects during collection. This is problematic for supporting native threads because an object can be relocated at any time, invalidating any references to the object. To prevent this either all threads must be stopped while major GC is running or a read barrier must be used each time an object is accessed. Both options add a potentially significant overhead so instead another type of collector is used for the second generation.
Cyclone supports native threads by using a tri-color tracing collector based on the Doligez-Leroy-Gonthier (DLG) algorithm for major collections. An advantage of this approach is that objects are not relocated once they are placed on the heap. In addition, major GC executes asynchronously so threads can continue to run concurrently even during collections.
More details are available in a separate [Garbage Collector](Garbage-collector.md) document.
### Native Thread Support
### Data Structures
TODO: code from Chibi scheme
TODO: not really related to this paper, but can allocation speedup for Cyclone be ported back to Chibi? Should look into that
## C Runtime
TODO: anything else to say about the C runtime???
yes, find that paper from Dybvig about writing Chez scheme, about how they made the runtime nice and fast. same applies here as well
here it is:
https://www.cs.indiana.edu/~dyb/pubs/hocs.pdf
The "money" quote is:
> My focus was instead on low-level details, like choosing efficient representations and generating good instruction sequences, and the compiler did include a peephole optimizer. High-level optimization is important, and we did plenty of that later, but low-level details often have more leverage in the sense that they typically affect a broader class of programs, if not all programs.
## Data Types
### Objects
Most Scheme data types are represented as allocated "objects" that contain a tag to identify the object type. For example:
typedef struct {tag_type tag; double value;} double_type;
### Value Types
On the other hand, some data types can be represented using 30 bits or less and can be stored as value types using a technique from Lisp in Small Pieces. On many machines, addresses are multiples of four, leaving the two least significant bits free. [A brief explanation](http://stackoverflow.com/q/9272526/101258):
> The reason why most pointers are aligned to at least 4 bytes is that most pointers are pointers to objects or basic types that themselves are aligned to at least 4 bytes. Things that have 4 byte alignment include (for most systems): int, float, bool (yes, really), any pointer type, and any basic type their size or larger.
Due to the tag field, all Cyclone objects will have (at least) 4-byte alignment.
Cyclone uses this technique to store characters. The nice thing about value types is they do not have to be garbage collected because no extra data is allocated for them.
## Interpreter
The [Metacircular Evaluator](https://mitpress.mit.edu/sicp/full-text/book/book-Z-H-26.html#%_sec_4.1) from [SICP](https://mitpress.mit.edu/sicp/full-text/book/book.html) was used as a starting point for `eval`.
TODO: explain analysis phase, and how this is a nice speedup
## Macros
[Explicit renaming](http://wiki.call-cc.org/explicit-renaming-macros) (ER) macros provide a simple, low-level macro system without requiring much more than `eval`. Many ER macros from [Chibi Scheme](https://github.com/ashinn/chibi-scheme) are used to implement the built-in macros in Cyclone.
TODO: syntax-rules ER macro from Chibi is used to provide support for this macro system
## Scheme Standards
Cyclone targets the [R<sup>7</sup>RS-small specification](https://github.com/justinethier/cyclone/raw/master/docs/r7rs.pdf). This spec is relatively new and provides incremental improvements from the popular [R<sup>5</sup>RS spec](http://www.schemers.org/Documents/Standards/R5RS/HTML/). Library (C module) support is the most important but there are also exceptions, system interfaces, and a more consistent API.
## Future
- Implement more of r7rs-large, have started on data structures
- implement more libraries (industria??)
- way to support eggs or other libraries? is that even worth the effort?
- benchmark
## Conclusion
TODO: this section is completely out of date, a better reference would be benchmark results from r7rs-benchmarks
From Feeley's presentation:
> Performance is not so bad with NO optimizations (about 6 times slower than Gambit-C with full optimization)
Compared to a similar compiler (CHICKEN), Cyclone's performance is worse but also "not so bad":
$ time cyclone -d transforms.sld
real 0m6.802s
user 0m4.444s
sys 0m1.512s
$ time csc -t transforms.scm
real 0m1.084s
user 0m0.512s
sys 0m0.380s
Thanks for reading!
Want to give Cyclone a try? Install a copy using [cyclone-bootstrap](https://github.com/justinethier/cyclone-bootstrap).
## References
- [CONS Should Not CONS Its Arguments, Part II: Cheney on the M.T.A.](http://www.pipeline.com/~hbaker1/CheneyMTA.html), by Henry Baker
- [CHICKEN Scheme](http://www.call-cc.org/)
- [Chibi Scheme](https://github.com/ashinn/chibi-scheme)
- [Compiling Scheme to C with closure conversion](http://matt.might.net/articles/compiling-scheme-to-c/), by Matt Might
- [Lisp in Small Pieces](http://pagesperso-systeme.lip6.fr/Christian.Queinnec/WWW/LiSP.html), by Christian Queinnec
- [R<sup>5</sup>RS Scheme Specification](http://www.schemers.org/Documents/Standards/R5RS/HTML/)
- [R<sup>7</sup>RS Scheme Specification](http://trac.sacrideo.us/wg/wiki)
- [Structure and Interpretation of Computer Programs](https://mitpress.mit.edu/sicp/full-text/book/book.html), by Harold Abelson and Gerald Jay Sussman
- [The 90 minute Scheme to C compiler](http://churchturing.org/y/90-min-scc.pdf), by Marc Feeley