Hello, I generate CnC++ code with a very large amount of steps, item and tag collections. The compilation times have grown to be unusably high. Currently, I'm metering the compilation time in different artificial scenarios. Currently I have only tested a deeply pipelined graph, a long chain of produce/consume steps. I was able to make some simple measurements on compilation time for gcc: (/usr/bin/time -f "%e %M" make)

I had a small window of opportunity to run my CnC++ code on a machine with a high number of processors and cores. Strangely enough, the performance graph was absolutely flat; the number of threads had no effect at all. The exact same code scales normally under the same linux OS on our single-socket 8-core machine. The benchmark results from "Performance Evaluation of Concurrent Collections
on High-Performance Multicore Computing Systems" do show scaling over NUMA machines, so I was wondering what I could do to make it run properly.

Please join us for CnC'11, the third annual Concurrent Collections workshop thats part of the 24th International Workshop on Languages and Compillers for Parallel Computing from September 7-10, 2011 at Colorado State University. Meet Kath Knobe, Intel Concurrent Collections Chief Scientist and learn more about Concurrent Collections.

Hi, I wrote a simple program that simple generates tags and processes them (attached below). However its performance degrades when I increase the number of threads. Would very appreciate any insight has to how/why to address the scalability issue. Thanks Sandeep //Stack.cnc ; ; :: (l1compute); :: (l2compute); env->; (l1compute)->;