> >How does python handle MT? > > Honestly? Really, really badly, at least from a performance point of view. > There's a single global lock and anything that might affect shared state > anywhere grabs it.
Python uses global lock for multi-threading. It is reasonable for io thread, which blocks most of time. It will completely useless for CPU intensive programs or large SMP machines. If Perl needs to have full multi-threading, we should better reference to Java. Java has the best language/runtime support for MT. It can run thousands of threads inside one VM on big SMP machine. However, Java has made many mistakes with threading. One of it is the synchronization overhead. A normal Java program can issue one million locks per second. The JDK 1.0.0 spent 20-25% of time in locking code when run HotJava. The main problem came from the fact the core library (Vector, Hashtable, IO streams, awt etc) are fully synchronized, even though most of time you don't need them to be synced. The same story may happen to Perl. If Perl make all operations on SV, AV, HV sync, the performance will be pathetic. Many SMP machines can only perform about 10M sync operations per second, because sync op requires system-wide bus lock or global memory transaction. This situation will not change much in the future. One way to reduce sync overhead is to make more operation atomic instead of of sync. For example, read() write() are atomic. There is no need to sync stream. The array get/put are atomic in Java, so we don't need sync either. The high level library or app itself will be responsible for the sync. Hong
