Process benchmark results with golang

Oh boy, I realy need to get out of the Moscovian airport, 15 hours is enough. But...

...at least it gave me some time to spare. After adding some MPI Benchmark results to my recent write-up. about my talk at HPC Advisory council I assume we all agree that the uglyness of my bash solution is endless.

Please cover your eyes, here we go one more time:

avg_2dig.sh

function doavg {
   echo "scale=2;($(echo $*|sed -e 's/ /+/g'))/$#"|bc
}


function avg2dig() {
    val=$(cat $1|egrep "^[0-9][0-9]?\s+[0-9\.]+$"|awk '{print $2}'|xargs)
    if [ "X${val}" != "X" ];then
        doavg  ${val}
    fi
}

$ source avg_2dig.sh # (1)!
$ for x in $(find job_results/mpi/ -name osu_alltoall.out|xargs);do 
    echo -n "$x -> "
    avg2dig $x
done|grep 1.8.3 # (2)!
job_results/mpi/venus/omp-1.8.3/2014-11-06_22-03-59/osu_alltoall.out -> 1.46
job_results/mpi/centos/7/omp-1.8.3/2014-11-06_22-05-33/osu_alltoall.out -> 1.41
job_results/mpi/centos/6/omp-1.8.3/2014-11-06_22-05-45/osu_alltoall.out -> 1.43
job_results/mpi/ubuntu/12/omp-1.8.3/2014-11-06_22-07-02/osu_alltoall.out -> 1.42

Sourcing the file to get the function ready to go
Not sure why I put the grep in the original post. Almost 10 years since then...

2min of bash coding and I am up and running. But that should not be the last word about the parsing.

One iteration to golang

What you are about to see is just one iteration towards happiness. I am going to reuse something I have done to parse the results of HPCG. To warn you upfront, I do not use interfaces, but a straight forward chain of functions. I guess this is still ugly, but less ugly then the bash version.

Let's call it "agile programming", a perfect excuse to not get it right in the first place... :P

Why oh why?

My first attempt was a small piece of python to parse the results. But since I had CentOS 6 and CentOS 7 I got python2.6 and python2.7. Let the dependency hell begin... With golang I am able to build a static binary - no strings attached - and I can forget about the target platform; at least if it is Linux 64bit, which is going to be the case. If not I can even crosscompile...

Basic concept

The fundamentals are easy. Within the job I fill a file job.cfg which stores key/value pairs given general information.

job.cfg

MPI_VER=omp-sys
BTL_OPTS=self,openib
DIRNAME=scripts/centos/7/omp-sys/mpi
OS_VER=7
OS_BASE=centos
SLURM_PARTITION=cos7
MPI_PATH=/usr/lib64/openmpi
START_DATE=2014-11-06_19:01:57
SLURM_NODELIST=cos7_[1-2]
SLURM_JOBID=627
WALL_CLOCK=0

Side note: Within golang I use my beloved docopt (I use it in python for some time now) to parse the command line arguments.

func main() {
    usage := `evaluate HPCG output

    Usage:
      eval-hpcg [options] <path>
      eval-hpcg -h | --help
      eval-hpcg --version

    Options:
      -h --help     Show this screen.
      --version     Show version.
    `
    var params map[string]string
    params = make(map[string]string)
    arguments, _ := docopt.Parse(usage, nil, true, "0.1", false)
    path := arguments["<path>"].(string)
    // enter directory
    walkDir(path, params)
}

The script (binary, that is!) is looking for a certain file (should be the job.cfg), provides the hook to evaluate certain output files (in a bit) and formats the result neatly.

$ go build && ./eval-osu-mpi ../../hpcac-job-results/mpi/
| MTIME:2014-11-07_09:01:21 | NODES:cos6_[1-2]      | MPI:omp-1.5.4  | WTIME:   2.0 | *WAIT_FOR_IT* |
| MTIME:2014-11-07_09:01:21 | NODES:cos6_[1-2]      | MPI:omp-1.6.4  | WTIME:   1.0 | *WAIT_FOR_IT* |

The *WAIT_FOR_IT* part is the customized part. For the MPI Benchmark we are looking out for files matching osu_(.*).out. Matching files are handed over to parseJobOut, which will process the bugger.

func parseJobOut(file_path string, subtest string) map[string]string {
    job_res := make(map[string]string)
    file_descr, err := os.Open(file_path)
    if err != nil {
        panic(err)
    }
    defer file_descr.Close()

    var res list.List
    if subtest == "alltoall" {
        // define pattern to look for
        re := regexp.MustCompile("([0-9]+)[\t ]+([0-9.]+)")
        scanner := bufio.NewScanner(file_descr)
        for scanner.Scan() {
            mat := re.FindStringSubmatch(scanner.Text())
                        // MAGIC HERE...
                        // Looking for lines matching and casting them to float64
        }

        // Iterate through list and sum up total
        var total float64 = 0
        for e := res.Front(); e != nil; e = e.Next() {
            total += e.Value.(float64)
        }
        avg := total / float64(res.Len())
        job_res["a2a_avg"] = fmt.Sprintf("%f", avg)
        if err := scanner.Err(); err != nil {
            log.Fatal(err)
        }
    }
    return job_res
}

In the print function, we now present the a2a average as an additional column.

func printDir(path string, params map[string]string) {
    job_cfg := evalResultDir(path)
    wtime, _ := strconv.ParseFloat(job_cfg["wall_clock"], 64)
    a2a_avg, _ := strconv.ParseFloat(job_cfg["a2a_avg"], 64)
    _, present := job_cfg["yaml_date"]
    if present {
        fmt.Printf("| YTIME:%s |", job_cfg["yaml_date"])
    } else {
        fmt.Printf("| MTIME:%s |", job_cfg["mod_time"])
    }
    fmt.Printf(" NODES:%-15s |", job_cfg["slurm_nodelist"])
    fmt.Printf(" MPI:%-10s |", job_cfg["mpi_ver"])
    fmt.Printf(" WTIME:%6.1f |", wtime)
    fmt.Printf(" A2A_AVG:%6.2f |", a2a_avg)  // HERE!!!
    fmt.Printf("\n")
}

And off we go...

$ go build && ./eval-osu-mpi ../../hpcac-job-results/mp | MTIME:2014-11-07_09:01:21 | NODES:cos6_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:cos6_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:cos6_[1-2] | MTIME:2014-11-06_21:42:21 | NODES:cos6_[1-2] | MTIME:2014-11-06_22:10:28 | NODES:cos6_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:cos7_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:cos7_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:cos7_[1-2] | MTIME:2014-11-06_21:42:21 | NODES:cos7_[1-2] | MTIME:2014-11-06_22:10:28 | NODES:cos7_[1-2] | MTIME:2014-11-06_22:10:28 | NODES:cos7_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:u12_[1-2] | MTIME:2014-11-07_09:01:21 | NODES:venus[001-002] | MTIME:2014-11-07_09:01:21 | NODES:venus[001-002] | MTIME:2014-11-07_09:01:21 | NODES:venus[001-002] | MTIME:2014-11-06_21:42:21 | NODES:venus[001-002] | MTIME:2014-11-06_21:42:21 | NODES:venus[001-002] | MTIME:2014-11-06_22:10:28 | NODES:venus[001-002] | MTIME:2014-11-06_22:10:28 | NODES:venus[001-002]

The sourcecode could be found here.

Process benchmark results with golang

One iteration to golang

Why oh why?

Basic concept

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