This contains my bachelors thesis and associated tex files, code snippets and maybe more. Topic: Data Movement in Heterogeneous Memories with Intel Data Streaming Accelerator
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

230 lines
7.1 KiB

{
"count": 8,
"list": [
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 119.9679,
"combined_stdev": 64.88604526084265,
"completion_avg": 118.9473,
"completion_stdev": 64.80201326124218,
"submission_avg": 0.371,
"submission_stdev": 1.9825133038647968,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 119.1021,
"combined_stdev": 65.27667022442458,
"completion_avg": 117.7053,
"completion_stdev": 64.86494316587202,
"submission_avg": 0.7823,
"submission_stdev": 2.92371453975974,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 78.9709,
"combined_stdev": 72.76109024190946,
"completion_avg": 78.0385,
"completion_stdev": 72.14649969159598,
"submission_avg": 0.2426,
"submission_stdev": 3.2682021418517553,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 119.09,
"combined_stdev": 64.95495285195577,
"completion_avg": 117.8331,
"completion_stdev": 64.7310686177006,
"submission_avg": 0.6662,
"submission_stdev": 2.9581713202577995,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 118.6519,
"combined_stdev": 65.31557185228132,
"completion_avg": 117.4566,
"completion_stdev": 64.8838956632572,
"submission_avg": 0.5441,
"submission_stdev": 2.8367331897803783,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 115.7251,
"combined_stdev": 64.07455914785389,
"completion_avg": 114.8225,
"completion_stdev": 63.51996059309606,
"submission_avg": 0.2007,
"submission_stdev": 2.680525976370031,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 119.0898,
"combined_stdev": 65.2489412631561,
"completion_avg": 117.6501,
"completion_stdev": 64.84477210993083,
"submission_avg": 0.8384,
"submission_stdev": 2.9953439602150453,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
},
{
"affinity": {
"nnode_dst": 0,
"nnode_src": 0,
"node": 0
},
"report": {
"iterations_completed": 10000,
"status": "ok",
"time": {
"combined_avg": 118.5125,
"combined_stdev": 65.22630331199869,
"completion_avg": 117.5606,
"completion_stdev": 64.70094533805663,
"submission_avg": 0.2538,
"submission_stdev": 2.8402439261442978,
"unit": "microseconds"
}
},
"task": {
"batching": {
"batch_size": 0,
"batch_submit": false
},
"iterations": 10000,
"size": 1048576
}
}
],
"path": "hw"
}