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Sometimes when you see an elegant algorithm, you think “looks great, I
just need it to also do X”. Perhaps you are able to build X directly
out of what the algorithm gives you; fantastic. Or, perhaps you can
alter the algorithm a bit, and it works just as well while also doing X.
Sometimes, though, you alter the algorithm and things go pear-shaped.
Tonight’s little note builds on yesterday’s semi-space collector
article
and discusses an worse alternative to the Cheney scanning algorithm.
To recall, we had this visit_field function that takes a edge in the
object graph, as the address of a field in memory containing a struct gc_obj*. If the edge points to an object that was already copied,
visit_field updates it to the forwarded address. Otherwise it copies the object,
thus computing the new address, and then updates the field.
struct gc_obj* copy(struct gc_heap *heap, struct gc_obj *obj) {
size_t size = heap_object_size(obj);
struct gc_obj *new_obj = (struct gc_obj*)heap->hp;
memcpy(new_obj, obj, size);
forward(obj, new_obj);
heap->hp += align_size(size);
return new_obj;
}
void visit_field(struct gc_obj **field, struct gc_heap *heap) {
struct gc_obj *from = *field;
struct gc_obj *to =
is_forwarded(from) ? forwarded(from) : copy(heap, from);
*field = to;
}
Although a newly copied object is in tospace, all of its fields
still point to fromspace. The Cheney scan algorithm later visits the
fields in the newly copied object with visit_field, which both
discovers new objects and updates the fields to point to tospace.
One disadvantage of this approach is that the order in which the objects
are copied is a bit random. Given a hierarchical memory system, it’s
better if objects that are accessed together in time are close together
in space. This is an impossible task without instrumenting the actual
data access in a program and then assuming future accesses will be like the
past. Instead, the generally-accepted solution is to ensure that
objects that are allocated close together in time be adjacent in
space. The bump-pointer allocator in a semi-space collector provides
this property, but the evacuation algorithm above does not: it would
need to preserve allocation order, but instead its order is driven by
graph connectivity.
I say that the copying algorithm above is random but really it favors a
breadth-first traversal; if you have a binary tree, first you will copy
the left and the right nodes of the root, then the left and right
children of the left, then the left and right children of the right,
then grandchildren, and so on. Maybe it would be better to keep parent
and child nodes together? After all they are probably allocated that
way.
So, what if we change the algorithm:
struct gc_obj* copy(struct gc_heap *heap, struct gc_obj *obj) {
size_t size = heap_object_size(obj);
struct gc_obj *new_obj = (struct gc_obj*)heap->hp;
memcpy(new_obj, obj, size);
forward(obj, new_obj);
heap->hp += align_size(size);
trace_heap_object(new_obj, heap, visit_field); // *
return new_obj;
}
void visit_field(struct gc_obj **field, struct gc_heap *heap) {
struct gc_obj *from = *field;
struct gc_obj *to =
is_forwarded(from) ? forwarded(from) : copy(heap, from);
*field = to;
}
Here we favor a depth-first traversal: we eagerly call
trace_heap_object within copy. No need for the Cheney scan
algorithm; tracing does it all.
void collect(struct gc_heap *heap) {
flip(heap);
uintptr_t scan = heap->hp;
trace_roots(heap, visit_field);
}
The thing is, this works! It might even have better performance for
some workloads, depending on access patterns. And yet, nobody does
this. Why?
Well, consider a linked list with a million nodes; you’ll end up with a
million recursive calls to copy, as visiting each link eagerly
traverses the next. While I am all about unbounded
recursion, an
infinitely extensible stack is something that a language runtime has to
provide to a user, and here we’re deep into
implementing-the-language-runtime territory. At some point a user’s
deep heap graph is going to cause a gnarly system failure via stack
overflow.
Ultimately stack space needed by a GC algorithm counts towards collector
memory overhead. In the case of a semi-space collector you already need
twice the amount memory as your live object graph, and if you recursed
instead of iterated this might balloon to 3x or more, depending on the
heap graph shape.
Hey that’s my note! All this has been context for some future article,
so this will be on the final exam. Until then!
