Changeset ddcaff6 for doc/theses/thierry_delisle_PhD/thesis/text/front.tex

Timestamp:

Nov 24, 2022, 3:41:44 PM (20 months ago)

Author:

Thierry Delisle <tdelisle@…>

Branches:

ADT, ast-experimental, master

Children:

dacd8e6e

Parents:

82a90d4

Message:

Last corrections to my thesis... hopefully

File:

• doc/theses/thierry_delisle_PhD/thesis/text/front.tex (modified) (2 diffs)

doc/theses/thierry_delisle_PhD/thesis/text/front.tex

@@ -88 +88 @@
         \\
         Internal Member: \> Martin Karsten \\
-        \> Associate Professor, School of Computer Science \\
+        \> Professor, School of Computer Science \\
         \> University of Waterloo \\
 \end{tabbing}
@@ -127 +127 @@
 Indeed, over-partitioning into small work-units with user threading significantly eases load bal\-ancing, while simultaneously providing advanced synchronization and mutual exclusion capabilities.
 To manage these high levels of concurrency, the underlying runtime must efficiently schedule many user threads across a few kernel threads;
-which begs the question of how many kernel threads are needed and should the number be dynamically reevaluated.
+which raises the question of how many kernel threads are needed and should the number be dynamically reevaluated.
 Furthermore, scheduling must prevent kernel threads from blocking, otherwise user-thread parallelism drops.
-When user-threading parallelism does drop, how and when should idle \glspl{kthrd} be put to sleep to avoid wasting CPU resources.
+When user-threading parallelism does drop, how and when should idle \glspl{kthrd} be put to sleep to avoid wasting CPU resources?
 Finally, the scheduling system must provide fairness to prevent a user thread from monopolizing a kernel thread;
 otherwise, other user threads can experience short/long term starvation or kernel threads can deadlock waiting for events to occur on busy kernel threads.