Instead of interpreting an expression, which is performing a full evaluation, we can think about compiling it: translating it to a different language which we can later run more easily, more efficiently, on more platforms, etc. Another feature that is usually associated with compilation is that a lot more work was done at the compilation stage, making the actual running of the code faster.
For example, translating an AST into one that has de-Bruijn indexes instead of identifier names is a form of compilation — not only is it translating one language into another, it does the work involved in name lookup before the program starts running.
This is something that we can experiment with now. An easy way to achieve this is to start with our evaluation function:
and change it so it compiles a given expression to a Racket function.
(This is, of course, just to demonstrate a conceptual point, it is only
the tip of what compilers actually do…) This means that we need to
turn it into a function that receives a TOY expression and compiles it.
In other words, eval no longer consumes and environment argument which
makes sense because the environment is a place to hold run-time values,
so it is a data structure that is not part of the compiler (it is
usually represented as the call stack).
So we split the two arguments into a compile-time and run-time, which
can be done by simply currying the eval function — here this is
done, and all calls to eval are also curried:
We also need to change the eval call in the main run function:
Not much has changed so far.
Note that in the general case of a compiler we need to run a program several times, so we’d want to avoid parsing it over and over again. We can do that by keeping a single parsed AST of the input. Now we went one step further by making it possible to do more work ahead and keep the result of the first “stage” of eval around (except that “more work” is really not saying much at the moment):
At this point, even though our “compiler” is not much more than a
slightly different representation of the same functionality, we rename
eval to compile which is a more appropriate description of what we
intend it to do (so we change the purpose statement too):
Not much changed, still. We curried the eval function and renamed it
to compile. But when we actually call compile almost nothing happens
— all it does is create a Racket closure which will do the rest of the
work. (And this closure closes over the given expression.)
Running this “compiled” code is going to be very much like the previous
usage of eval, except a little slower, because now every recursive
call involves calling compile to generate a closure, which is then
immediately used — so we just added some allocations at the recursive
call points! (Actually, the extra cost is minimal because the Racket
compiler will optimize away such immediate closure applications.)
Another way to see how this is not really a compiler yet is to consider
when compile gets called. A proper compiler is something that does
all of its work before running the code, which means that once it
spits out the compiled code it shouldn’t be used again (except for
compiling other code, of course). Our current code is not really a
compiler since it breaks this feature. (For example, if GCC behaved
this way, then it would “compile” files by producing code that invokes
GCC to compile the next step, which, when run, invokes GCC again, etc.)
However, the conceptual change is substantial — we now have a function that does its work in two stages — the first part gets an expression and can do some compile-time work, and the second part does the run-time work, and includes anything inside the (lambda (env) …). The thing is that so far, the code does nothing at the compilation stage (remember: only creates a closure). But because we have two stages, we can now shift work from the second stage (the run-time) to the first (the compile-time).
For example, consider the following simple example:
We can do the same thing here — separate foo it into two stages
using currying, and modify bar appropriately:
Now instead of a simple multiplication, lets expand it a little, for
example, do a case split on common cases where x is 0, 1, or 2:
This is not much faster, since Racket already optimizes multiplication in a similar way.
Now comes the real magic: deciding what branch of the cond to take
depends only on x, so we can push the lambda inside:
We just made an improvement — the comparisons for the common cases are
now done as soon as (foo x) is called, they’re not delayed to when the
resulting function is used. Now go back to the way this is used in
bar and make it call foo once for the given c:
Now foo-c is generated once, and if c happens to be one of the three
common cases (as in the last expression), we can avoid doing any
multiplication. (And if we hit the default case, then we’re doing the
same thing we did before.)
[However, the result runs a little slower! The reason is that dealing with functions can have a higher cost when the compiler cannot “simplify closures away” — and this is what happens in the last version. The additional overhead is much higher than the multiplication we save (the Racket compiler inlines multiplications, so their cost is close to just executing a single machine-code instruction).]
Here is another useful example that demonstrates this:
(Question: when can you do that?)
This is not unique to Racket, it can happen in any language. Racket (or any language with first class function values) only makes it easy to create a local function that is specialized for the flag.
Getting our thing closer to a compiler is done in a similar way — we
push the (lambda (env) ...) inside the various cases. (Note that
compile* depends on the env argument, so it also needs to move
inside — this is done for all cases that use it, and will eventually
go away.) We actually need to use (lambda ([env : ENV]) ...) though,
to avoid upsetting the type checker:
and with this we shifted a bit of actual work to compile time — the
code that checks what structure we have, and extracts its different
slots. But this is still not good enough — it’s only the first
top-level cases that is moved to compile-time — recursive calls to
compile are still there in the resulting closures. This can be seen
by the fact that we have those calls to compile in the Racket closures
that are the results of our compiler, which, as discussed above, mean
that it’s not an actual compiler yet.
For example, consider the Bind case:
At compile-time we identify and deconstruct the Bind structure, then
create a the runtime closure that will access these parts when the code
runs. But this closure will itself call compile on bound-body and
each of the expressions. Both of these calls can be done at compile
time, since they only need the expressions — they don’t depend on the
environment. Note that compile* turns to run here, since all it
does is run a compiled expression on the current environment.
We can move it back up, out of the resulting functions, by making it a function that consumes an environment and returns a “caller” function:
Once this is done, we have a bunch of work that can happen at compile time: we pre-scan the main “bind spine” of the code.
We can deal in a similar way with other occurrences of compile calls
in compiled code. The two branches that need to be fixed are:
In the If branch, there is not much to do. After we make it
pre-compile the cond-expr, we also need to make it pre-compile both
the then-expr and the else-expr. This might seem like doing more
work (since before changing it only one would get compiled), but
since this is compile-time work, then it’s not as important. Also,
if expressions are evaluated many times (being part of a loop, for
example), so overall we still win.
The Call branch is a little trickier: the problem here is that the
expressions that are compiled are coming from the closure that is
being applied. The solution for this is obvious: we need to change
the closure type so that it closes over compiled expressions
instead of over plain ones. This makes sense because closures are
run-time values, so they need to close over the compiled expressions
since this is what we use as “code” at run-time.
Again, the goal is to have no compile calls that happen at runtime:
they should all happen before that. This would allow, for example, to
obliterate the compiler once it has done its work, similar to how you
don’t need GCC to run a C application. Yet another way to look at this
is that we shouldn’t look at the AST at runtime — again, the analogy
to GCC is that the AST is a data structure that the compiler uses, and
it does not exist at runtime. Any runtime reference to the TOY AST is,
therefore, as bad as any runtime reference to compile.
When we’re done with this process we’ll have something that is an actual compiler: translating TOY programs into Racket closures. To see how this is an actual compiler consider the fact that Racket uses a JIT to translate bytecode into machine code when it’s running functions. This means that the compiled version of our TOY programs are, in fact, translated all the way down to machine code.
Yet another way to see this is to change the compiler code so instead of producing a Racket closure it spits out the Racket code that makes up these closures when evaluated. For example, change
into
so we get a string that is a Racket program. But since we’re using a Lisp dialect, it’s generally better to use S-expressions instead:
(Later in the course we’ll talk about these “`“s and “,“s. For
now, it’s enough to know that “`” is kind of like a quote, and
“,” is an unquote.)