AndiH

% See: https://tex.stackexchange.com/a/387460/56326
% \usepackage[minted]{tcolorbox}
% \tcbuselibrary{skins}
\definecolor{topbar}{RGB}{220,220,220}
\definecolor{main}{RGB}{30,30,30}
\definecolor{quit}{RGB}{248,73,73}
\definecolor{min}{RGB}{252,182,37}
\definecolor{max}{RGB}{41,198,52}
\colorlet{offwhite}{white!96!black}
\newtcblisting{fauxshell}{%

AndiH

AndiH

AndiH

# import inspect
from __future__ import print_function

class Counter(object):
	"""Simple counter, counting an invocation my means of a string (explicit call) or function name (decorator)"""

	counters = {}
	def __init__(self, *args, **kwargs):
		"""Construct class. First, check if class is called via a decorator or directly. If true, defer incrementing counter until wrapped function is actually called (see __call__). If false, increment counter now."""
		if callable(args[0]):

AndiH

#!/bin/bash
# This file sets the environment variable CUDA_VISIBLE_DEVICES to the MPI local rank to enable multi-GPU usage of this benchmark. Note that this disables any GPU distribution handling by he batch scheduler.
# Background: Most/some batch schedulers set CUDA_VISIBLE_DEVICES to all available GPUs on a node. In that case, the Arbor benchmark would only use the first entry in the list, probably GPU#0. This script changes that.
# -Andreas Herten, Nov 2018

_verbose=1

localrank=$CUDA_VISIBLE_DEVICES

if [[ -n "$OMPI_COMM_WORLD_NODE_RANK" ]]; then

AndiH

#!/usr/bin/make -f
# Makefile for installing Tensorflow
#
# -Andreas Herten, 1 Feb 2019

SHELL = /bin/bash

NAME = tensorflow

VERSION = 1.12.0

AndiH

#!/usr/bin/env bash

_SYSTEMNAME=$(cat /etc/FZJ/systemname)
USERSHELL=/bin/zsh

case $_SYSTEMNAME in
  juron)
    export SYSTEMNAME="JURON"
  ;;
  juwels)

AndiH

omp_id

AndiH

#!/usr/bin/make -f
# Makefile for installing OpenMPI
#
# -Andreas Herten, 15 Dec 2017

SHELL = /bin/bash


PRGNAME = openmpi
VERSION = 4.0.1

AndiH