{"id":675,"date":"2019-11-19T18:18:43","date_gmt":"2019-11-19T17:18:43","guid":{"rendered":"http:\/\/server.philipheinisch.com\/wordpress\/?page_id=675"},"modified":"2024-03-02T22:49:55","modified_gmt":"2024-03-02T21:49:55","slug":"home-3","status":"publish","type":"page","link":"https:\/\/ianw.de\/index.php\/home-3\/","title":{"rendered":"IANW-EN"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"675\" class=\"elementor elementor-675\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fdf1307 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fdf1307\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-bf06dbf\" data-id=\"bf06dbf\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-eab7135 elementor-widget elementor-widget-text-editor\" data-id=\"eab7135\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-size: 15px;\">The Institut\u00a0f\u00fcr angewandte numerische Wissenschaft e.V. (Institute for Applied Numerical Science, IANW) is a nonprofit research institute engaging in the development and application of numerical methods. Several technologies ranging from artificial intelligence via blockchain up to computational fluid dynamics are based on numerical methods, making these essential for both economy and science.<\/span><\/p><p><span style=\"font-size: 15px;\">The goal of the IANW is to combine and apply recent results from computer science, physics, and mathematics. Thereby, new numerical methods are developed and applied in practice. Another focus is the development and application of novel tools for simple and efficient usage of modern heterogeneous hardware systems.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f09ec48 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f09ec48\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-3d8b9f0\" data-id=\"3d8b9f0\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7b712d6 elementor-widget elementor-widget-heading\" data-id=\"7b712d6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Numerical Methods<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-gpj1hy3 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"gpj1hy3\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-qqbe2op big-margin\" data-id=\"qqbe2op\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dxnutd9 elementor-widget elementor-widget-text-editor\" data-id=\"dxnutd9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Many models in physics, science, and engineering are very complex and necessitate numerical methods to approximate solutions. These include for example the computation of air flows, the analysis of inflammation processes in the human body, and the simulation of defibrillators.<\/p><p><span style=\"font-size: 15px;\">To satisfy the increasing demands, numerical methods have to be improved continuously. For balance laws in continuum physics and phenomena such as turbulence, high order methods play an important role. To be able to cope with current and future challenges, their robustness and stability have to be ensured.<\/span><\/p><p><span style=\"font-size: 15px;\">In this context, plasma physics is in the current\u00a0 research focus of the IANW. In particular, the simulation of phenomena in the\u00a0 magnetosphere of the earth and the influence of\u00a0inhomogeneities are of interest.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-3018efb\" data-id=\"3018efb\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7c524ea elementor-hidden-desktop elementor-hidden-tablet elementor-widget elementor-widget-image\" data-id=\"7c524ea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1131\" height=\"1084\" src=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/plot_Taylor_Green_Vorticity_Order_6_N_128_transparent.png\" class=\"attachment-full size-full wp-image-412\" alt=\"\" srcset=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/plot_Taylor_Green_Vorticity_Order_6_N_128_transparent.png 1131w, https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/plot_Taylor_Green_Vorticity_Order_6_N_128_transparent-300x288.png 300w, https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/plot_Taylor_Green_Vorticity_Order_6_N_128_transparent-768x736.png 768w, https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/plot_Taylor_Green_Vorticity_Order_6_N_128_transparent-1024x981.png 1024w\" sizes=\"(max-width: 1131px) 100vw, 1131px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6ccb2df elementor-hidden-phone elementor-widget elementor-widget-video\" data-id=\"6ccb2df\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;video_type&quot;:&quot;hosted&quot;,&quot;autoplay&quot;:&quot;yes&quot;,&quot;loop&quot;:&quot;yes&quot;,&quot;mute&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"e-hosted-video elementor-wrapper elementor-open-inline\">\n\t\t\t\t\t<video class=\"elementor-video\" src=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/06\/video_Taylor_Green.mp4\" autoplay=\"\" loop=\"\" muted=\"muted\" controlsList=\"nodownload\"><\/video>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-06cd157 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"06cd157\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d83c769\" data-id=\"d83c769\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c205183 elementor-widget elementor-widget-heading\" data-id=\"c205183\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Machine Learning<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-78c28a0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"78c28a0\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-77249c3\" data-id=\"77249c3\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2e7e158 elementor-widget elementor-widget-image\" data-id=\"2e7e158\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"864\" height=\"432\" src=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/detection_res_1.gif\" class=\"attachment-full size-full wp-image-529\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Patterns characterized by a steep edge directly followed by a slowly decaying edge are recognized. Symmetrical pulses and square waves are ignored.<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-368f3a4 big-margin\" data-id=\"368f3a4\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a71731d elementor-widget elementor-widget-text-editor\" data-id=\"a71731d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Because of the ever-increasing amount of data, machine learning has gained more and more in prominence over recent years. Facilitated by the immense increase in computational power over the last years, mainly in the form of GPUs, it was possible to implement efficient algorithms, e.g. in the area of image recognition and natural language processing.<\/p><p>Motivated by this recent progress, the IANW researches the application and development of methods for automated data analysis in the context of large scale physics projects. Thereby, the implementation of these methods on various hardware is an integral part. One main focus is the automated recognition of patterns in time series for large scale statistical studies or process monitoring.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-9e5c8bd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9e5c8bd\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5b62a57\" data-id=\"5b62a57\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1f4821b elementor-widget elementor-widget-heading\" data-id=\"1f4821b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">High Performance Computing<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-qwp06n8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"qwp06n8\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-oje3xcf big-margin\" data-id=\"oje3xcf\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-17a77d3 elementor-widget elementor-widget-text-editor\" data-id=\"17a77d3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The performance increase of modern hardware systems is based on massive parallelization. Numerous concepts and software implementations are available to make use of these features, which makes choosing the right approach challenging. \u00a0Therefore, the IANW is developing tools to help with the implementation and application of parallel algorithms.<\/p><p><span style=\"font-family: Roboto, sans-serif; font-size: 15px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: bold;\">Machine learning and highly complex simulations for physics and engineering applications are based on executing similar operations on large datasets. The IANW is developing corresponding software to measure and optimize runtime and energy efficiency of different algorithms depending on the hardware platform.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2331fa4\" data-id=\"2331fa4\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-57f5845 elementor-widget elementor-widget-image\" data-id=\"57f5845\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"473\" height=\"500\" src=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/cpu.png\" class=\"attachment-full size-full wp-image-583\" alt=\"\" srcset=\"https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/cpu.png 473w, https:\/\/ianw.de\/wp-content\/uploads\/2019\/05\/cpu-284x300.png 284w\" sizes=\"(max-width: 473px) 100vw, 473px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>The Institut\u00a0f\u00fcr angewandte numerische Wissenschaft e.V. (Institute for Applied Numerical Science, IANW) is a nonprofit research institute engaging in the development and application of numerical methods. Several technologies ranging from artificial intelligence via blockchain up to computational fluid dynamics are based on numerical methods, making these essential for both economy and science. The goal of [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"ocean_post_layout":"full-screen","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"0","ocean_second_sidebar":"0","ocean_disable_margins":"on","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"0","ocean_custom_header_template":"0","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"0","ocean_menu_typo_font_family":"0","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"on","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"0","footnotes":""},"class_list":["post-675","page","type-page","status-publish","hentry","entry"],"acf":[],"_links":{"self":[{"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/pages\/675","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/comments?post=675"}],"version-history":[{"count":27,"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/pages\/675\/revisions"}],"predecessor-version":[{"id":745,"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/pages\/675\/revisions\/745"}],"wp:attachment":[{"href":"https:\/\/ianw.de\/index.php\/wp-json\/wp\/v2\/media?parent=675"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}