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+ .style("fill", cfg.color(series)).style("fill-opacity", .9)
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+</script>
+<script type="text/javascript">window.onload = function() {
+ var cpu = 88.6;
+ var mpi = 11.4;
+ var io = 0.0;
+
+ // Draw radar chart, choose its color based on application classification
+ var radar_data = [[ { axis: "CPU", value: cpu },
+ { axis: "MPI", value: mpi },
+ { axis: "I/O", value: io } ]];
+ var radar_options = { w: 200, h: 200, factor: 0.7, fontSize: 16, radius: 0,
+ opacityArea: 0.64, maxValue: 100,
+ color: function() {
+ if ("cpu" == "io") return "#ed8140";
+ if ("cpu" == "cpu") return "#4fd32e";
+ if ("cpu" == "mpi") return "#409ded";
+ else return "#bb58d6";
+ }
+ };
+ RadarChart.draw("#time_radar", radar_data, radar_options);
+
+ // Wrap the exe path on slashes if necessary
+ var exe_path = document.getElementById("exe_path");
+ exe_path.innerHTML = exe_path.innerHTML.replace(/\//g, '/​'); // insert a zero width space after slashes as a word wrap hint
+
+ // Format our byte value numbers to show at most 2 decimal places, but only if required to attain 3 digits of precision
+ // 1234.56 -> "1234"
+ // 12.3456 -> "12.3"
+ // 1.23456 -> "1.23"
+ // 0.00000 -> "0.00"
+ var formatNumber = function(num) {
+ if (num > 100) return new Number(num).toFixed(0); // 1234.56 -> 1234
+ if (num > 10) return new Number(num).toFixed(1); // 12.3456 -> 12.3
+ else return new Number(num).toFixed(2); // 1.23456 -> 1.23 and 0 -> 0.00
+ }
+
+ // Parse a number, but return 0 for invalid numbers, not NaN
+ var toNumber = function(num_str) {
+ var num = Number(num_str)
+ return isNaN(num) ? 0 : num;
+ }
+
+ // Scale byte values to bytes, kB, MB or GB as appropriate
+ var fillBytes = function(base_name, bytes_str, per_second) {
+ var units = "bytes";
+ var scale = 1.0;
+ var bytes = Number(bytes_str)
+ if (isNaN(bytes) ) { units = "" ; }
+ else if (bytes > 1000000000) { units = "GB"; scale = 1*1000*1000*1000; }
+ else if (bytes > 1000000 ) { units = "MB"; scale = 1*1000*1000 }
+ else if (bytes > 1000 ) { units = "kB"; scale = 1*1000 }
+ var num = isNaN(bytes) ? bytes_str : formatNumber(bytes / scale);
+ var elementNum = document.getElementById(base_name + "_num");
+ elementNum.innerHTML = num;
+ var elementUnits = document.getElementById(base_name + "_units");
+ elementUnits.innerHTML = units + (per_second && !isNaN(bytes) ? "/s" : "");
+ };
+
+ // Fill all the byte numbers and their units with the scaled values
+ fillBytes("mpi_colrate", "1.65e+02", true);
+ fillBytes("mpi_p2prate", "0.00e+00", true);
+ fillBytes("io_readrate", "0.00e+00", true);
+ fillBytes("io_writerate", "0.00e+00", true);
+ fillBytes("ram_mean", "2.33e+07", false);
+ fillBytes("ram_peak", "2.35e+07", false);
+
+ // Set widths for all graphs
+ var bar = function(name, width) {
+ var rounded = Math.round(width);
+ if (!isFinite(rounded) || rounded < 1)
+ document.getElementById(name).style.width = "1px"
+ else
+ document.getElementById(name).style.width = rounded + "px";
+ };
+ bar("cpu_bar", cpu * 2);
+ bar("mpi_bar", mpi * 2);
+ bar("io_bar", io * 2);
+
+ bar("cpu_num_bar", toNumber("50.0") / 2);
+ bar("cpu_vec_bar", toNumber("50.0") / 2);
+ bar("cpu_mem_bar", toNumber("0.0") / 2);
+ bar("cpu_other_bar", toNumber("0.0") / 2);
+
+ bar("mpi_col_bar", toNumber("100.0") / 2);
+ bar("mpi_p2p_bar", toNumber("0.0") / 2);
+ var mpi_scale = Math.max(toNumber("1.65e+02"), toNumber("0.00e+00"));
+ bar("mpi_colrate_bar", 50 * toNumber("1.65e+02") / mpi_scale);
+ bar("mpi_p2prate_bar", 50 * toNumber("0.00e+00") / mpi_scale);
+
+ bar("io_read_bar", toNumber("0.0") / 2);
+ bar("io_write_bar", toNumber("0.0") / 2);
+ var io_scale = Math.max(toNumber("0.00e+00"), toNumber("0.00e+00"));
+ bar("io_readrate_bar", 50 * toNumber("0.00e+00") / io_scale);
+ bar("io_writerate_bar", 50 * toNumber("0.00e+00") / io_scale);
+
+ bar("ram_mean_bar", 50 * toNumber("2.33e+07") / toNumber("2.35e+07"));
+ bar("ram_peak_bar", 50);
+ bar("ram_node_bar", toNumber("2.8") / 2);
+
+ // Formatting replacement helper function
+ var replaceIn = function(elementId, re, new_text) {
+ element = document.getElementById(elementId);
+ element.innerHTML = element.innerHTML.replace(re, new_text);
+ };
+
+ // Add formatting for the overview advice section
+ replaceIn('overview_advice', /CPU/g, '<span class="cpu_span">CPU</span>');
+ replaceIn('overview_advice', /MPI/g, '<span class="mpi_span">MPI</span>');
+ replaceIn('overview_advice', /I\/O/g, '<span class="io_span">I\/O</span>');
+
+ // Add formatting for the CPU advice section
+ if ( 88.6 < 0.05 )
+ replaceIn('cpu_explanation', /application code/g, '<span class="cpu_span">application code</span>');
+ replaceIn('cpu_explanation', /vectorized instructions/g, '<span class="cpu_vec_span">vectorized instructions</span>');
+ replaceIn('cpu_explanation', /memory accesses/g, '<span class="cpu_mem_span">memory accesses</span>');
+ replaceIn('cpu_explanation', /memory-bound/g, '<span class="cpu_mem_span">memory-bound</span>');
+ replaceIn('cpu_explanation', /arithmetic-bound/g, '<span class="cpu_num_span">arithmetic-bound</span>');
+ replaceIn('cpu_explanation', /numerical computation/g, '<span class="cpu_num_span">numerical computation</span>');
+
+ // Add formatting for the MPI advice section
+ if ( 11.4 < 0.05 )
+ replaceIn('mpi_explanation', /MPI/g, '<span class="mpi_span">MPI</span>');
+ replaceIn('mpi_explanation', /collective calls/g, '<span class="mpi_col_span">collective calls</span>');
+ replaceIn('mpi_explanation', /point-to-point calls/g, '<span class="mpi_p2p_span">point-to-point calls</span>');
+ replaceIn('mpi_explanation', / very low/g, ' <span class="mpi_colrate_span">very low</span>');
+ replaceIn('mpi_explanation', / low/g, ' <span class="mpi_colrate_span">low</span>');
+ replaceIn('mpi_explanation', / average/g, ' <span class="mpi_colrate_span">average</span>');
+ replaceIn('mpi_explanation', / very high/g, ' <span class="mpi_colrate_span">very high</span>');
+ replaceIn('mpi_explanation', / high/g, ' <span class="mpi_colrate_span">high</span>');
+
+ // Add formatting for the I/O advice section
+ if ( 0.0 < 0.05 )
+ replaceIn('io_explanation', /I\/O/g, '<span class="io_span">I/O</span>');
+ replaceIn('io_explanation', /read operations/g, '<span class="io_read_span">read operations</span>');
+ replaceIn('io_explanation', /write operations/g, '<span class="io_write_span">write operations</span>');
+ replaceIn('io_explanation', / very low/g, ' <span class="io_readrate_span">very low</span>');
+ replaceIn('io_explanation', / low/g, ' <span class="io_readrate_span">low</span>');
+ replaceIn('io_explanation', / average/g, ' <span class="io_readrate_span">average</span>');
+ replaceIn('io_explanation', / very high/g, ' <span class="io_readrate_span">very high</span>');
+ replaceIn('io_explanation', / high/g, ' <span class="io_readrate_span">high</span>');
+
+ // Add formatting for the RAM advice section
+ replaceIn('ram_explanation', /high/g, ' <span class="ram_node_span">high</span>');
+ replaceIn('ram_explanation', /well-balanced/g, '<span class="ram_peak_span">well-balanced</span>');
+ replaceIn('ram_explanation', /significant variation/g, '<span class="ram_peak_span">significant variation</span>');
+ replaceIn('ram_explanation', /peak node memory usage/g, '<span class="ram_node_span">peak node memory usage</span>');
+
+ // Hide the error warning if the script got this far
+ document.getElementById('error').style.display = 'none';
+};
+</script>
+</head>
+
+<body>
+<div id="content">
+
+<div class="header">
+ <div class="logo"><img src="http://content.allinea.com/downloads/performance-report-logo.png" alt="Allinea Performance Reports" /></div>
+ <div class="header_left">
+ <div class="application_details">
+ <table>
+ <tr><td class="details_key">Executable:</td><td id="exe_name">mympiprog.x</td></tr>
+ <tr><td class="details_key">Resources:</td><td id="num_procs">32 processes, 2 nodes</td></tr>
+ <tr><td class="details_key">Machine:</td><td id="machine_name">cn182</td></tr>
+ <tr><td class="details_key">Start time:</td><td id="start_date">Wed Oct 15 16:56:23 2014</td></tr>
+ <tr><td class="details_key">Total time:</td><td id="time_string">7 seconds (0 minutes)</td></tr>
+ <tr><td class="details_key">Full path:</td><td id="exe_path">/home/user</td></tr>
+ <tr><td class="details_key">Notes:</td><td id="notes"></td></tr>
+ </table>
+ </div>
+ </div>
+ <div id="time_radar"></div>
+ <div class="clear"></div>
+</div>
+<hr />
+<div id="error">
+<p><strong>Error: javascript is not running</strong></p>
+<p>The graphs in this Performance Report require <strong>javascript</strong>, which is disabled or not working.</p>
+<p>Check whether your javascript support is enabled or try another browser.<p>
+<p>Remember, you can always contact <a href="mailto:support@allinea.com">support@allinea.com</a>, we're very nice!</p>
+</div>
+<div class="summary">
+ <div class="heading">Summary: mympiprog.x is <span class="cpu_span">CPU-bound</span> in this configuration</div>
+ <div>The total wallclock time was spent as follows:</div>
+ <table class="summary_table">
+ <tr><td class="heading_cpu">CPU</td><td class="percent">88.6%</td><td class="bar_graph"><div id="cpu_bar" /></td>
+ <td class="details"><p>Time spent running application code. High values are usually good.</p><p>This is <span id="summary_cpu_class">high</span>; check the CPU performance section for optimization advice.</p></td></tr>
+ <tr><td class="heading_mpi">MPI</td><td class="percent">11.4%</td><td class="bar_graph"><div id="mpi_bar" /></td>
+ <td class="details"><p>Time spent in MPI calls. High values are usually bad.</p><p>This is <span id="summary_mpi_class">very low</span>; this code may benefit from increasing the process count.</p></td></tr>
+ <tr><td class="heading_io">I/O</td><td class="percent">0.0%</td><td class="bar_graph"><div id="io_bar" /></td>
+ <td class="details"><p>Time spent in filesystem I/O. High values are usually bad.</p><p>This is <span id="summary_io_class">negligible</span>; there's no need to investigate I/O performance.</p></td></tr>
+ </table>
+ <div class="overview_general_advice"><p>This application run was <span class="cpu_span">CPU-bound</span>. A breakdown of this time and advice for investigating further is in the <span class="cpu_span">CPU</span> section below.</p><p id="overview_advice">As very little time is spent in MPI calls, this code may also benefit from running at larger scales.</p></div>
+</div>
+<hr />
+<div class="subsections">
+ <div class="ltcol">
+ <div class="heading_cpu">CPU</div>
+ <div>A breakdown of how the <span class="cpu_span">88.6</span>% total CPU time was spent:</div>
+ <table id="cpu_chart">
+ <tr><td>Scalar numeric ops</td><td class="right_cell"><span class="cpu_num_span">50.0</span>%</td><td class="mini_bar_graph"><div id="cpu_num_bar" /></td></tr>
+ <tr><td>Vector numeric ops</td><td class="right_cell"><span class="cpu_vec_span">50.0</span>%</td><td class="mini_bar_graph"><div id="cpu_vec_bar" /></td></tr>
+ <tr><td>Memory accesses</td><td class="right_cell"><span class="cpu_mem_span">0.0</span>%</td><td class="mini_bar_graph"><div id="cpu_mem_bar" /></td></tr>
+ <tr><td>Other</td><td class="right_cell"><span class="cpu_other_span">0.0</span>%</td><td class="mini_bar_graph"><div id="cpu_other_bar" /></td></tr>
+ </table>
+ <div id="cpu_explanation">
+ <div class="explanation">The per-core performance is arithmetic-bound. Try to increase the amount of time spent in vectorized instructions by analyzing the compiler's vectorization reports.</div>
+ <div class="explanation"></div>
+ </div>
+ </div>
+ <div class="rtcol">
+ <div class="heading_mpi">MPI</div>
+ <div>Of the <span class="mpi_span">11.4</span>% total time spent in MPI calls:</div>
+ <table id="mpi_chart">
+ <tr><td>Time in collective calls</td><td class="right_cell"><span class="mpi_col_span">100.0</span>%</td><td class="mini_bar_graph"><div id="mpi_col_bar" /></td></tr>
+ <tr><td>Time in point-to-point calls</td><td class="right_cell"><span class="mpi_p2p_span">0.0</span>%</td><td class="mini_bar_graph"><div id="mpi_p2p_bar" /></td></tr>
+ <tr><td>Effective process collective rate</td><td class="right_cell"><span class="mpi_colrate_span"><span id="mpi_colrate_num">1.65e+02</span></span> <span id="mpi_colrate_units"></span></td><td class="mini_bar_graph"><div id="mpi_colrate_bar" /></td></tr>
+ <tr><td>Effective process point-to-point rate</td><td class="right_cell"><span class="mpi_p2prate_span"><span id="mpi_p2prate_num">0.00e+00</span></span> <span id="mpi_p2prate_units"></span></td><td class="mini_bar_graph"><div id="mpi_p2prate_bar" /></td></tr>
+ </table>
+ <div id="mpi_explanation">
+ <div class="explanation">Most of the time is spent in collective calls with a very low transfer rate. This suggests load imbalance is causing synchonization overhead; use an MPI profiler to investigate further.</div>
+ <div class="explanation"></div>
+ </div>
+ </div>
+ <div class="clear"></div>
+</div>
+<div class="subsections">
+ <div class="ltcol">
+ <div class="heading_io">I/O</div>
+ <div>A breakdown of how the <span class="io_span">0.0</span>% total I/O time was spent:</div>
+ <table id="io_chart">
+ <tr><td>Time in reads</td><td class="right_cell"><span class="io_read_span">0.0</span>%</td><td class="mini_bar_graph"><div id="io_read_bar" /></td></tr>
+ <tr><td>Time in writes</td><td class="right_cell"><span class="io_write_span">0.0</span>%</td><td class="mini_bar_graph"><div id="io_write_bar" /></td></tr>
+ <tr><td>Effective process read rate</td><td class="right_cell"><span class="io_readrate_span"><span id="io_readrate_num">0.00e+00</span></span> <span id="io_readrate_units"></span></td><td class="mini_bar_graph"><div id="io_readrate_bar" /></td></tr>
+ <tr><td>Effective process write rate</td><td class="right_cell"><span class="io_writerate_span"><span id="io_writerate_num">0.00e+00</span></span> <span id="io_writerate_units"></span></td><td class="mini_bar_graph"><div id="io_writerate_bar" /></td></tr>
+ </table>
+ <div id="io_explanation">
+ <div class="explanation">No time is spent in I/O operations. There's nothing to optimize here!</div>
+ <div class="explanation"></div>
+ </div>
+ </div>
+ <div class="rtcol">
+ <div class="heading_ram">Memory</div>
+ <div>Per-process memory usage may also affect scaling:</div>
+ <table id="ram_chart">
+ <tr><td>Mean process memory usage</td><td class="right_cell"><span class="ram_mean_span"><span id="ram_mean_num">2.33e+07</span></span> <span id="ram_mean_units"></span></td><td class="mini_bar_graph"><div id="ram_mean_bar" /></td></tr>
+ <tr><td>Peak process memory usage</td><td class="right_cell"><span class="ram_peak_span"><span id="ram_peak_num">2.35e+07</span></span> <span id="ram_peak_units"></span></td><td class="mini_bar_graph"><div id="ram_peak_bar" /></td></tr>
+ <tr><td>Peak node memory usage</td><td class="right_cell"><span class="ram_node_span">2.8</span>%</td><td class="mini_bar_graph"><div id="ram_node_bar" /></td></tr>
+ </table>
+ <div id="ram_explanation">
+ <div class="explanation">The peak node memory usage is very low. You may be able to reduce the amount of allocation time used by running with fewer MPI processes and more data on each process.</div>
+ <div class="explanation"></div>
+ </div>
+ </div>
+ <div class="clear"></div>
+</div>
+</div> <!-- content -->
+</body>
+</html>
diff --git a/docs.it4i/src/mympiprog_32p_2014-10-15_16-56.txt b/docs.it4i/src/mympiprog_32p_2014-10-15_16-56.txt
new file mode 100644
index 0000000000000000000000000000000000000000..de8449179640fd943a9f007f9eda084b11f2a455
--- /dev/null
+++ b/docs.it4i/src/mympiprog_32p_2014-10-15_16-56.txt
@@ -0,0 +1,50 @@
+Executable: mympiprog.x
+Resources: 32 processes, 2 nodes
+Machine: cn182
+Started on: Wed Oct 15 16:56:23 2014
+Total time: 7 seconds (0 minutes)
+Full path: /home/user
+Notes:
+
+Summary: mympiprog.x is CPU-bound in this configuration
+CPU: 88.6% |========|
+MPI: 11.4% ||
+I/O: 0.0% |
+This application run was CPU-bound. A breakdown of this time and advice for investigating further is found in the CPU section below.
+As very little time is spent in MPI calls, this code may also benefit from running at larger scales.
+
+CPU:
+A breakdown of how the 88.6% total CPU time was spent:
+Scalar numeric ops: 50.0% |====|
+Vector numeric ops: 50.0% |====|
+Memory accesses: 0.0% |
+Other: 0.0% |
+The per-core performance is arithmetic-bound. Try to increase the amount of time spent in vectorized instructions by analyzing the compiler's vectorization reports.
+
+
+MPI:
+A breakdown of how the 11.4% total MPI time was spent:
+Time in collective calls: 100.0% |=========|
+Time in point-to-point calls: 0.0% |
+Effective collective rate: 1.65e+02 bytes/s
+Effective point-to-point rate: 0.00e+00 bytes/s
+Most of the time is spent in collective calls with a very low transfer rate. This suggests load imbalance is causing synchonization overhead; use an MPI profiler to investigate further.
+
+
+I/O:
+A breakdown of how the 0.0% total I/O time was spent:
+Time in reads: 0.0% |
+Time in writes: 0.0% |
+Effective read rate: 0.00e+00 bytes/s
+Effective write rate: 0.00e+00 bytes/s
+No time is spent in I/O operations. There's nothing to optimize here!
+
+
+Memory:
+Per-process memory usage may also affect scaling:
+Mean process memory usage: 2.33e+07 bytes
+Peak process memory usage: 2.35e+07 bytes
+Peak node memory usage: 2.8% |
+The peak node memory usage is very low. You may be able to reduce the amount of allocation time used by running with fewer MPI processes and more data on each process.
+
+