optimize for training

Author: Graeme22

cluster.jl

@@ -36,8 +36,11 @@ end
 
 choose_index(wl::Workload) = rand(1:length(wl.jobs) - SLICE_SIZE)
 
+# load all workloads into memory; about 3GB
+workloads = [Workload(wl) for wl in WORKLOADS]
+
 function RLBase.reset!(env::ClusterEnv)
-    workload = Workload(rand(WORKLOADS))
+    workload = rand(workloads)
     env.workload = workload
     index = choose_index(workload)
     env.time = env.workload.jobs[1].submit_time
@@ -54,7 +57,7 @@ function RLBase.reset!(env::ClusterEnv)
 end
 
 function ClusterEnv()
-    workload = Workload(rand(WORKLOADS))
+    workload = rand(workloads)
     index = choose_index(workload)
     time = workload.jobs[1].submit_time
     next_job_index = index + 1

data/HPC2N-2002-2.2-cln.swf

@@ -33,7 +33,7 @@
 ; sjf_average_wait: 12791.929f0
 ; sjf_max_wait: 1631664
 ; sjf_utilization: 0.39929992f0
-    
+
 ;
 ;
 ; Note: THIS IS A CLEANED VERSION OF THE LOG!

data/LANL-CM5-1994-4.1-cln.swf

@@ -49,7 +49,7 @@
 ; sjf_average_wait: 17167.924f0
 ; sjf_max_wait: 7661244
 ; sjf_utilization: 0.26229486f0
-  
+
 ;
 ; Note: THIS IS A CLEANED VERSION OF THE LOG!
 ;       The filters used to produce it were