Frog is Asynchronous Graph Processing on GPU with Hybrid Coloring Model. The fundamental idea is based on Pareto principle (or 80-20 rule) about coloring algorithms as we observed through masses of real graph coloring cases.
Hello,
I ran the Frog framework exp executable on the V100 and K40 GPU by changing -arch=sm_20 in the Makefile to support -arch=sm_70 and -arch=sm_35 respectively. I also enabled the non-partitioned option by uncommenting gpu_sssp_edge_loop in sssp.cu, gpu_bfs_edge_loop in bfs.cu and gpu_cc_edge_loop in cc.cu. The graph used in the experiment is com-youtube which can be found here: https://sparse.tamu.edu/SNAP/com-Youtube
This is the result of running ./exp
The left side of the graph is Frog running on V100, right side is Frog on K40. All of the runs are check PASS . My concern is: it looks like for all runs, the non-partitioned implementations outperform the partitioned implementation. I cannot produce results where the asynchronous model (with coloring as partitioning scheme) outperform the bulk-sync model. Please let me know if I am doing something wrong.
Hello, I ran the Frog framework
expexecutable on the V100 and K40 GPU by changing-arch=sm_20in theMakefileto support-arch=sm_70and-arch=sm_35respectively. I also enabled the non-partitioned option by uncommentinggpu_sssp_edge_loopinsssp.cu,gpu_bfs_edge_loopinbfs.cuandgpu_cc_edge_loopincc.cu. The graph used in the experiment is com-youtube which can be found here: https://sparse.tamu.edu/SNAP/com-YoutubeThis is the result of running
./expThe left side of the graph is Frog running on V100, right side is Frog on K40. All of the runs are
check PASS. My concern is: it looks like for all runs, the non-partitioned implementations outperform the partitioned implementation. I cannot produce results where the asynchronous model (with coloring as partitioning scheme) outperform the bulk-sync model. Please let me know if I am doing something wrong.Thank you!