Wire up the JS engine's memory reporting.

SpiderMonkey provides an extremely fine-grained breakdown of memory
usage, but for Servo we aggregate the measurements into a small number
of coarse buckets, which seems appropriate for the current level of
detail provided by Servo's memory profiler. Sample output:
```
|   10.99 MiB -- pages
|       7.75 MiB -- url(http://html5demos.com/worker)
|          4.63 MiB -- js
|             2.00 MiB -- gc-heap
|                0.94 MiB -- decommitted
|                0.92 MiB -- used
|                0.09 MiB -- unused
|                0.05 MiB -- admin
|             1.44 MiB -- malloc-heap
|             1.19 MiB -- non-heap
|          [...]
|       3.24 MiB -- url(http://html5demos.com/js/worker-cruncher.js)
|          3.24 MiB -- js
|             1.17 MiB -- malloc-heap
|             1.06 MiB -- non-heap
|             1.00 MiB -- gc-heap
|                0.69 MiB -- used
|                0.19 MiB -- decommitted
|                0.09 MiB -- unused
|                0.03 MiB -- admin
```
Most of the changes are plumbing to get the script and worker tasks
communicating with the memory profiler task.

1 files changed, 2 insertions, 2 deletions

diff --git a/components/script/dom/worker.rs b/components/script/dom/worker.rs
index 34e07a6ee91..257ecbdcef1 100644
--- a/components/script/dom/worker.rs
+++ b/components/script/dom/worker.rs
@@ -90,8 +90,8 @@ impl Worker {
         }
 
         DedicatedWorkerGlobalScope::run_worker_scope(
-            worker_url, global.pipeline(), global.devtools_chan(), worker_ref, resource_task, global.script_chan(),
-            sender, receiver);
+            worker_url, global.pipeline(), global.mem_profiler_chan(), global.devtools_chan(),
+            worker_ref, resource_task, global.script_chan(), sender, receiver);
 
         Ok(worker)
     }