Accelerated Machine Learning Platform

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none">Model iteration adds overhead</h3> <div class="description color-black body-text"><p>Iteration means waiting for results to return and spending more on compute power. 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tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h2 class="title color-brand-green h2 uppercase" >Advancing the Machine Learning Ecosystem</h2> <div class="description color-black body-text"><p>NVIDIA offers solutions to accelerate your business’ machine learning operations, whether you’re building a new model from scratch or fine-tuning the performance of critical business-enabling processes. NVIDIA provides solutions that combine hardware and software optimized for high-performance machine learning to make it easy for businesses to generate illuminating insights out of their data. With RAPIDS and NVIDIA CUDA, data scientists can accelerate machine learning pipelines on NVIDIA GPUs, reducing machine learning operations like data loading, processing, and training from days to minutes. 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Labels will * be split into lines on "\n", extra padding will be added between * bars, and font will be smaller to accommodate the extra line. * Supported options: * "" - For default styling, leaving labels as single lines. * "two-lines" - Both lines will be slightly smaller in font than default. * "title-subtitle" - Second line will be smaller than first line. * @param isDark - true to enable styling for dark background, otherwise false. */ function createHorizontalBarChart(chartContainer, data, ticks, xAxisLabel, yAxisLabelClass, isDark) { var barAnimationDuration = 1000; var animationDelay = 200; var chart = drawHorizontalBarChart(chartContainer, data, ticks, xAxisLabel, yAxisLabelClass, isDark); // If the chart should be immediately visible, begin animation. var rendered = false; if (chartContainer.node().getBoundingClientRect().top - window.innerHeight <= 0) { rendered = true; animate(chart, barAnimationDuration, animationDelay); } // Begin animation the first time the chart scrolls into view. window.addEventListener("scroll", function() { if (!rendered && chartContainer.node().getBoundingClientRect().top - window.innerHeight <= 0) { rendered = true; animate(chart, barAnimationDuration, animationDelay); } }); // Redraw whenever the browser window is resized. var width = window.innerWidth; window.addEventListener("resize", function() { if (window.innerWidth != width) { chartContainer.selectAll("*").remove(); drawHorizontalBarChart(chartContainer, data, ticks, xAxisLabel, yAxisLabelClass, isDark); width = window.innerWidth; } }); } function drawHorizontalBarChart(chartContainer, data, ticks, xAxisLabel, yAxisLabelClass, isDark) { // Right margin leaves room for last tick label var margin = {top: 0, right: 20, bottom: 0, left: 0}; var barHeight = 20; var barPadding = 5; if (yAxisLabelClass == "two-lines" || yAxisLabelClass == "title-subtitle") { barPadding = 10; } var tickPadding = 12; var lineHeight = 1.1; // ems var svg = chartContainer.append("svg"); // The graph's width is set to fit within its parent container. var svgWidth = svg.node().parentNode.getBoundingClientRect().width; svg.attr("width", svgWidth); if (isDark) { svg.attr("class", yAxisLabelClass + " dark"); } else { svg.attr("class", yAxisLabelClass); } // The graph's height is a function of the number of bars. var height = (barHeight * data.length + barPadding * (data.length + 1)); var g = svg.append("g").attr("class", "graph"); var y = d3.scaleBand().range([0, height]); y.domain(data.map(function(d) { return d.axisLabel; })) .padding(0.2); // Draw the y axis to know how much space to leave for it, // then immediately delete it. Redrawing it last ensures // the correct ordering of layers for display. drawYAxis(g, y, tickPadding, lineHeight, yAxisLabelClass); var yAxisWidth = svg.select(".y").node().getBoundingClientRect().width; svg.select("g.y.axis").remove(); var width = svgWidth - margin.left - yAxisWidth - margin.right; g.attr("transform", "translate(" + (yAxisWidth + margin.left) + "," + margin.top + ")"); var x = d3.scaleLinear().range([0, width]); x.domain([d3.min(ticks, function(d) { return d.value; }), d3.max(ticks, function(d) { return d.value; })]); var xAxis = d3.axisBottom(x) .tickValues(ticks.map(function(tick) { return tick.value; })) .tickFormat(function(d, i) { return ticks[i].tickLabel; }) .tickSizeInner([-height]) .tickSizeOuter(0) .tickPadding(tickPadding); g.append("g") .attr("class", "x axis tick-label") .attr("transform", "translate(0," + height + ")") .call(xAxis); svg.selectAll(".x .tick").each(function(t, i) { d3.select(this).attr("class", ticks[i].class); }); var greenBegin = "#76b900"; var greenEnd = "#c8e399"; if (isDark) { greenEnd = "#3b5d00"; } var greenScale = d3.interpolateLab(greenBegin, greenEnd); var numGreens = 0; for (var i = 0; i < data.length; i++) { if (data[i].class == "green") { numGreens++; } } var bars = g.selectAll(".bar") .data(data).enter().append("g") .attr("transform", function(d, i) { return "translate(0," + y(d.axisLabel) + ")"; }); bars.append("rect") .attr("class", function(d) { return "bar " + d.class; }) .attr("fill", function(d, i) { if (d.class == "green") { return greenScale(i/numGreens); } }) .attr("x", 0) .attr("height", barHeight) .attr("width", function(d) { return x(d.value); }); // Add labels on bars var barLabels = bars.append("text") .attr("class", "bar-label") .attr("x", function(d) { return x(d.value) - 6; }) .attr("y", barHeight / 2) .attr("dy", ".35em") .text(function(d) { return d.barLabel; }); barLabels.each(function(d, i) { if (this.getBoundingClientRect().width + 12 > bars.nodes()[i].getBoundingClientRect().width) { var labelWidth = this.getBoundingClientRect().width; var bar = d3.select(this.parentNode).select(".bar"); var barWidth = bar.node().getBoundingClientRect().width; if (labelWidth + 13 > width - barWidth) { this.remove(); } else { d3.select(this) .attr("transform", "translate(" + 12 + ",0)") .attr("class","outer-bar-label") .style("text-anchor", "start"); } } }); var xAxisHeight = svg.select(".x.axis.tick-label").node().getBoundingClientRect().height; // Add a label to the x axis. if (xAxisLabel) { g.append("text") .attr("x", width / 2) .attr("y", xAxisHeight + 5) .attr("class", "axis-label") .attr("alignment-baseline", "hanging") .text(xAxisLabel) .call(wrap, width, lineHeight); } drawYAxis(g, y, tickPadding, lineHeight, yAxisLabelClass); var svgHeight = margin.top + margin.bottom + svg.select(".graph").node().getBoundingClientRect().height; svg.attr("height", svgHeight); return { svg: svg, data: data, x: x, }; } /** * Add a grouped horizontal bar chart to the provided svg element. * * @param svg - A d3 selection of the svg to add the chart to. * @param legend - A d3 selection of the div to add the legend to. * @param barData - One row per horizontal bar, each with attributes * "label", "values". * @param legendData - One row per horizontal bar, each with attributes * "label" and "class". * E.g. For a two-bar chart comparing Quadro P5000 to CPU: * [ * {"label": "Quadro P5000", "class": "green"}, * {"label": "CPU", "class": "green"} * ] * @param ticks - The ticks to show on the x-axis, each with attributes * "tickLabel", "value", and "class". * E.g. For 3 ticks, with the middle tick hidden for mobile: * [ * {"tickLabel": "0", "value": 0, "class": ""}, * {"tickLabel": "1X", "value": 1, "class": "mobile-hide"}, * {"tickLabel": "2X", "value": 2, "class": ""} * ] * @param milestone - Optional, an object with a "color" and "value" * for a milestone line in the chart. Set null for no milestone. * @param xAxisLabel - The label to show under the x axis. * @param isDark - true to enable styling for dark background, otherwise false. */ function createGroupedHorizontalBarChart(chartContainer, barData, legendData, ticks, milestone, xAxisLabel, isDark) { var barAnimationDuration = 800; var animationDelay = 30; var chart = drawHorizontalGroupedBarChart(chartContainer, barData, legendData, ticks, milestone, xAxisLabel, isDark); // If the chart should be immediately visible, begin animation. var rendered = false; if (chartContainer.node().getBoundingClientRect().top - window.innerHeight <= 0) { rendered = true; animate(chart, barAnimationDuration, animationDelay); } // Begin animation the first time the chart scrolls into view. window.addEventListener("scroll", function() { if (!rendered && chartContainer.node().getBoundingClientRect().top - window.innerHeight <= 0) { rendered = true; animate(chart, barAnimationDuration, animationDelay); } }); // Redraw whenever the browser window is resized. var width = window.innerWidth; window.addEventListener("resize", function() { if (window.innerWidth != width) { chartContainer.selectAll("*").remove(); drawHorizontalGroupedBarChart(chartContainer, barData, legendData, ticks, milestone, xAxisLabel, isDark); width = window.innerWidth; } }); } function drawHorizontalGroupedBarChart(chartContainer, barData, legendData, ticks, milestone, xAxisLabel, isDark) { // Right margin leaves room for last tick label var margin = {top: 0, right: 20, bottom: 0, left: 0}; var barHeight = 10; var barPadding = 2; var groupPadding = 10; var tickPadding = 12; var lineHeight = 1.1; var keys = legendData.map(function(l) { return l.label; }); var legend = chartContainer.append("div"); var svg = chartContainer.append("svg"); var greenBegin = "#76b900"; var greenEnd = "#c8e399"; if (isDark) { greenEnd = "#3b5d00"; } var greenScale = d3.interpolateLab(greenBegin, greenEnd); var numGreens = 0; for (var i in legendData) { if (legendData[i].class == "green") { numGreens++; } } // The graph's width is set to fit within its parent container. var svgWidth = svg.node().parentNode.getBoundingClientRect().width; svg.attr("width", svgWidth); if (isDark) { svg.attr("class", "dark"); legend.attr("class", "legend dark"); } else { legend.attr("class", "legend"); } // The graph's height is a function of the number of bars. var height = (barHeight * legendData.length * barData.length + groupPadding * (barData.length + 1) + barPadding * (legendData.length - 1) * barData.length); var g = svg.append("g").attr("class", "graph"); // Map groups to graph height var y0 = d3.scaleBand().range([0, height]).padding(0.1); y0.domain(barData.map(function(d) { return d.label; })); // Map bars to group height var y1 = d3.scaleBand().padding(0.2); y1.domain(keys).range([0, y0.bandwidth()]); // Draw the y axis to know how much space to leave for it, // then immediately delete it. Redrawing it last ensures // the correct ordering of layers for display. drawYAxis(g, y0, tickPadding, lineHeight, null); var yAxisWidth = svg.select(".y").node().getBoundingClientRect().width; svg.select("g.y.axis").remove(); var width = svgWidth - margin.left - yAxisWidth - margin.right; g.attr("transform", "translate(" + (yAxisWidth + margin.left) + "," + margin.top + ")"); var x = d3.scaleLinear().range([0, width]); x.domain([0, d3.max(ticks, function(d) { return d.value; })]); var xAxis = d3.axisBottom(x) .tickValues(ticks.map(function(tick) { return tick.value; })) .tickFormat(function(d, i) { return ticks[i].tickLabel; }) .tickSizeInner([-height]) .tickSizeOuter(0) .tickPadding(tickPadding); g.append("g") .attr("class", "x axis tick-label") .attr("transform", "translate(0," + height + ")") .call(xAxis); var z = d3.scaleOrdinal() .range(legendData.map(function(l) { return l.class; })) .domain(keys); // Add a label to the x axis. var xAxisHeight = svg.select(".x.axis.tick-label").node().getBoundingClientRect().height; // Add a label to the x axis. if (xAxisLabel) { g.append("text") .attr("x", width / 2) .attr("y", xAxisHeight + 5) .attr("class", "axis-label") .attr("alignment-baseline", "hanging") .text(xAxisLabel) .call(wrap, width, lineHeight); } g.append("g") .selectAll("g") .data(barData) .enter().append("g") .attr("transform", function(d) { return "translate(0," + y0(d.label) + ")"; }) .selectAll("rect") .data(function(d) { return keys.map(function(key, i) { return {key: key, value: d.values[i]}; }); }) .enter().append("rect") .attr("class", function(d) { return z(d.key) + " bar"; }) .attr("y", function(d, i) { return y1(d.key) }) .attr("x", function(d) { return 0; }) .attr("height", barHeight) .attr("width", function(d, i) { return x(d.value); }) .attr("fill", function(d, i) { if (z(d.key) == "green") { return greenScale(i / numGreens); } }) .attr("width", function(d) { return x(d.value); }); // Add milestone line if (milestone) { // It appears D3 adds .5 to ticks to get crispEdges for Safari // (see https://github.com/d3/d3-axis/issues/8) var milestoneX = x(milestone.value) + .5; g.append("line") .attr("class", "milestone " + milestone.class) .attr("x1", milestoneX) .attr("x2", milestoneX) .attr("y1", 0) .attr("y2", height); } addLegend(legend, legendData, milestone, greenScale, numGreens); drawYAxis(g, y0, tickPadding, lineHeight, null); var svgHeight = margin.top + margin.bottom + svg.select(".graph").node().getBoundingClientRect().height; svg.attr("height", svgHeight); return { svg: svg, x: x, }; } </script><div id="starting-grouped-chart"></div> <script> var chart = d3.select("#starting-grouped-chart"); var legendData = [ {"label": "1M", "class": "green"}, {"label": "2M", "class": "green"}, {"label": "4M", "class": "green"}, ]; var barData = [ {"label": "PCA", "values": [64, 120, 0]}, {"label": "Linear Regression", "values": [24, 46, 69]}, {"label": "Ridge", "values": [17, 24, 46]}, {"label": "TSVD", "values": [9.7, 15, 22]}, {"label": "SGD", "values": [9.5, 11, 12]}, {"label": "Lasso", "values": [4.6, 5.5, 6.6]}, {"label": "ElasticNet", "values": [4.2, 5.4, 5.9]}, ]; var ticks = [ {"value": 0, "tickLabel": "0", "class": ""}, {"value": 20, "tickLabel": "20", "class": ""}, {"value": 40, "tickLabel": "40", "class": ""}, {"value": 60, "tickLabel": "60", "class": ""}, {"value": 80, "tickLabel": "80", "class": ""}, {"value": 100, "tickLabel": "100", "class": ""}, {"value": 120, "tickLabel": "120", "class": ""}, ] // Specify "value" and "color" of milestone line. // Set null for no milestone line. var milestone = {"label": "", "value": null, "class": ""}; var xAxisLabel = "GPU Speedup Over CPU"; var isDark = false; createGroupedHorizontalBarChart(chart, barData, legendData, ticks, milestone, xAxisLabel, isDark); </script> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-12 medium-6 large-6 "> <div class=""></div> <div 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Integration with leading data science frameworks like Apache Spark, cuPY, Dask, XGBoost, and Numba, as well as numerous deep learning frameworks, such as PyTorch, TensorFlow, and Apache MxNet, broaden adoption and encourage integration with others. Through GPU-acceleration, machine learning ecosystem innovations like <a href="https://rapids.ai/hpo" target="_blank" rel="noopener noreferrer">RAPIDS hyperparameter optimization (HPO)</a> and <a href="https://medium.com/rapids-ai/sparse-forests-with-fil-ffbb42b0c7e3" target="_blank" rel="noopener noreferrer">RAPIDS Forest Inferencing Library (FIL)</a> are reducing once time consuming operations to a matter of seconds.</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"><div class="button parbase section"> <div class="text-center lap-text-center tab-text-center mob-text-center p-t-15 p-b-15 lap-p-t-15 lap-p-b-15 tab-p-t-15 tab-p-b-15 mob-p-t-15 mob-p-b-15 mobile-align "> <div class="noicon " > <a href='https://www.nvidia.com/en-sg/deep-learning-ai/software/rapids/' data-analytics="txt-manual:" data-title="" data-href='https://www.nvidia.com/en-sg/deep-learning-ai/software/rapids/' target="_self" class=' link-txt txt-manual brand-green regular-btn ' 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