{"id":2682,"date":"2021-10-11T13:38:45","date_gmt":"2021-10-11T17:38:45","guid":{"rendered":"https:\/\/labs.icahn.mssm.edu\/minervalab\/?page_id=2682"},"modified":"2026-03-03T12:52:35","modified_gmt":"2026-03-03T17:52:35","slug":"scientific-computing-and-data","status":"publish","type":"page","link":"https:\/\/labs.icahn.mssm.edu\/minervalab\/scientific-computing-and-data\/","title":{"rendered":"Scientific Computing and Data"},"content":{"rendered":"<p>[et_pb_section bb_built=&#8221;1&#8243; admin_label=&#8221;%22Scientific Computing and Data%22 page header block&#8221; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221; background_image=&#8221;https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2022\/05\/block-bg-gradient-221f72.png&#8221; animation_style=&#8221;zoom&#8221; animation_intensity_zoom=&#8221;8%&#8221; animation_starting_opacity=&#8221;100%&#8221; next_background_color=&#8221;#ffffff&#8221;][et_pb_row _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221;][et_pb_text admin_label=&#8221;%22Scientific Computing and Data%22 &#8221; _builder_version=&#8221;4.9.0&#8243; text_font=&#8221;||||||||&#8221; text_text_color=&#8221;#ffffff&#8221; text_font_size=&#8221;18px&#8221; text_line_height=&#8221;1.8em&#8221; header_font=&#8221;|700|||||||&#8221; header_text_align=&#8221;center&#8221; header_text_color=&#8221;#ffffff&#8221; header_font_size=&#8221;35px&#8221; header_line_height=&#8221;1.3em&#8221; header_2_font=&#8221;||||||||&#8221; text_orientation=&#8221;center&#8221; max_width=&#8221;700px&#8221; module_alignment=&#8221;center&#8221;]<\/p>\n<h1>Scientific Computing and Data<\/h1>\n<p>Partnering with researchers to advance scientific discovery<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=&#8221;1&#8243; admin_label=&#8221;%22Get Started%22 block&#8221; 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header_text_align=&#8221;center&#8221; header_text_color=&#8221;#535b7c&#8221; header_2_font=&#8221;|700|||||||&#8221; header_2_text_color=&#8221;#221f72&#8243; header_2_font_size=&#8221;35px&#8221; header_2_line_height=&#8221;1.3em&#8221; text_orientation=&#8221;center&#8221; max_width=&#8221;700px&#8221; module_alignment=&#8221;center&#8221;]<\/p>\n<h2>Advance your Science<\/h2>\n<p>Utilize our services to facilitate your research, data, or compute power.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row admin_label=&#8221;Features Row&#8221; column_structure=&#8221;1_4,1_4,1_4,1_4&#8243; use_custom_gutter=&#8221;on&#8221; gutter_width=&#8221;2&#8243; _builder_version=&#8221;3.25&#8243; custom_padding=&#8221;|||&#8221;][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;3.25&#8243; background_color_gradient_direction=&#8221;243deg&#8221; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_blurb admin_label=&#8221;HPC&#8221; title=&#8221;High Performance Computing&#8221; 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body_link_text_shadow_blur_strength_tablet=&#8221;1px&#8221; body_ul_text_shadow_horizontal_length=&#8221;body_ul_text_shadow_style,%91object Object%93&#8243; body_ul_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; body_ul_text_shadow_vertical_length=&#8221;body_ul_text_shadow_style,%91object Object%93&#8243; body_ul_text_shadow_vertical_length_tablet=&#8221;0px&#8221; body_ul_text_shadow_blur_strength=&#8221;body_ul_text_shadow_style,%91object Object%93&#8243; body_ul_text_shadow_blur_strength_tablet=&#8221;1px&#8221; body_ol_text_shadow_horizontal_length=&#8221;body_ol_text_shadow_style,%91object Object%93&#8243; body_ol_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; body_ol_text_shadow_vertical_length=&#8221;body_ol_text_shadow_style,%91object Object%93&#8243; body_ol_text_shadow_vertical_length_tablet=&#8221;0px&#8221; body_ol_text_shadow_blur_strength=&#8221;body_ol_text_shadow_style,%91object Object%93&#8243; body_ol_text_shadow_blur_strength_tablet=&#8221;1px&#8221; body_quote_text_shadow_horizontal_length=&#8221;body_quote_text_shadow_style,%91object Object%93&#8243; body_quote_text_shadow_horizontal_length_tablet=&#8221;0px&#8221; body_quote_text_shadow_vertical_length=&#8221;body_quote_text_shadow_style,%91object Object%93&#8243; body_quote_text_shadow_vertical_length_tablet=&#8221;0px&#8221; body_quote_text_shadow_blur_strength=&#8221;body_quote_text_shadow_style,%91object Object%93&#8243; body_quote_text_shadow_blur_strength_tablet=&#8221;1px&#8221; border_width_top_tablet=&#8221;6px&#8221; border_width_top_phone=&#8221;6px&#8221; vertical_offset_tablet=&#8221;0&#8243; horizontal_offset_tablet=&#8221;0&#8243; z_index_tablet=&#8221;0&#8243;]<\/p>\n<p><strong>The primary asset for Scientific Computing is the supercomputer, Minerva<\/strong>:<\/p>\n<ul>\n<li><strong>Upgraded<\/strong>: November 2024 and February 2026.<\/li>\n<li><strong>Computing power<\/strong>: &gt;20 petaflops.<\/li>\n<li><strong>25,584 Intel Platinum processors in different generations<\/strong>\n<ul>\n<li>2.1 GHz, 2.3 GHz, 2.6 GHz, and 2.9 GHz computing cores with 1.5 terabytes (TB) or 2 terabytes (TB) of memory per node<\/li>\n<li>112 cores or 96 cores or 64 cores or 48 cores per node with two sockets in each node<\/li>\n<\/ul>\n<\/li>\n<li><strong>408 graphics processing units (GPUs)<\/strong>\n<ul>\n<li>48 Nvidia B200s, 236 Nvidia H100s, 32 Nvidia L40S, 44 Nvidia A100s, 48 Nvidia V100s<\/li>\n<li>452 TB of total memory<\/li>\n<li>32 petabytes of spinning storage accessed via IBM\u2019s Spectrum Scale\/General Parallel File System (GPFS)<\/li>\n<\/ul>\n<\/li>\n<li><strong>Contributed to &gt;2,100 peer-reviewed publications since 2012<\/strong>.<\/li>\n<\/ul>\n<p>[\/et_pb_blurb][\/et_pb_column][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;4.9.0&#8243; _module_preset=&#8221;default&#8221;][et_pb_blurb admin_label=&#8221;AIR\u00b7MS&#8221; title=&#8221;AIR\u00b7MS (Artificial Intelligence-Ready Mount Sinai)&#8221; image=&#8221;https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2025\/04\/AIR-MS-Logo.jpg&#8221; _builder_version=&#8221;4.9.0&#8243; header_level=&#8221;h2&#8243; header_font=&#8221;|600|||||||&#8221; header_text_color=&#8221;#221f72&#8243; header_line_height=&#8221;1.4em&#8221; body_font=&#8221;||||||||&#8221; body_text_color=&#8221;#959baf&#8221; body_font_size=&#8221;16px&#8221; body_line_height=&#8221;1.1em&#8221; background_color=&#8221;#ffffff&#8221; text_orientation=&#8221;center&#8221; custom_margin=&#8221;|||&#8221; custom_padding=&#8221;54px|20px|60px|20px&#8221; animation_style=&#8221;zoom&#8221; animation_intensity_zoom=&#8221;10%&#8221; border_radii=&#8221;on|4px|4px|4px|4px&#8221; border_color_all=&#8221;#00aeef&#8221; border_width_top=&#8221;6px&#8221; border_color_top=&#8221;#221f72&#8243; box_shadow_style=&#8221;preset3&#8243; box_shadow_color=&#8221;rgba(34,56,101,0.12)&#8221;]<\/p>\n<p style=\"text-align: left\">AIR\u00b7MS is a cloud-based, multi-modal health data platform that integrates patient data generated from different clinical departments across Health Systems. At this time, the following datasets are offered on the platform:<\/p>\n<p class=\"et_pb_toggle_title\" style=\"text-align: left\"><strong><a href=\"https:\/\/labs.icahn.mssm.edu\/msdw\/about-us\/\">Mount Sinai Data Warehouse (MSDW)<\/a><\/strong><\/p>\n<div class=\"et_pb_toggle_content clearfix\" style=\"text-align: left\">\n<ul>\n<li>Uses the\u202f<a href=\"https:\/\/www.ohdsi.org\/data-standardization\/the-common-data-model\/\" target=\"blank\" rel=\"noopener\">OMOP Common Data Model<\/a>.<\/li>\n<li>Clinical data extracted from Mount Sinai\u2019s Epic Caboodle database.<\/li>\n<li>Both identifiable and de-identified versions of the MSDW dataset are offered in AIR\u00b7MS.<\/li>\n<\/ul>\n<p class=\"et_pb_toggle_title\"><strong>Clinical Notes<\/strong><\/p>\n<ul>\n<li class=\"et_pb_toggle_content clearfix\">Clinical notes in the form of unstructured data (progress notes, telephone encounters, nursing notes, procedures, etc.)<\/li>\n<li class=\"et_pb_toggle_content clearfix\">In-memory full-text search capabilities (SAP HANA database management) have been enabled to empower researchers to build patient cohorts based on terms contained in unstructured reports in seconds or even milliseconds!<\/li>\n<\/ul>\n<\/div>\n<div>\n<p class=\"et_pb_toggle_title\" style=\"text-align: left\"><strong>Computational Pathology<\/strong><\/p>\n<ul>\n<li class=\"et_pb_toggle_content clearfix\" style=\"text-align: left\">The pathology metadata will aid researchers in the field of\u00a0<a href=\"https:\/\/mtsinai.sharepoint.com\/sites\/HPIMS\/SitePages\/Computational-Pathology.aspx\" target=\"blank\" rel=\"noopener\">Computational Pathology<\/a>.<\/li>\n<li class=\"et_pb_toggle_content clearfix\" style=\"text-align: left\">Researchers will be able to build their patient cohort across data modalities and subsequently apply quantitative methods for the analysis of digital microscopy slides relating the resulting statistical descriptors to patient outcomes.<\/li>\n<\/ul>\n<\/div>\n<p>[\/et_pb_blurb][\/et_pb_column][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;3.25&#8243; background_color_gradient_direction=&#8221;243deg&#8221; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_blurb admin_label=&#8221;RDS&#8221; title=&#8221;Research Data Services&#8221; image=&#8221;https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2021\/10\/RDS-150&#215;150.png&#8221; _builder_version=&#8221;4.9.0&#8243; header_level=&#8221;h2&#8243; header_font=&#8221;|600|||||||&#8221; header_text_color=&#8221;#221f72&#8243; header_line_height=&#8221;1.4em&#8221; body_font=&#8221;||||||||&#8221; body_text_color=&#8221;#959baf&#8221; body_font_size=&#8221;16px&#8221; body_line_height=&#8221;1.1em&#8221; background_color=&#8221;#ffffff&#8221; text_orientation=&#8221;center&#8221; custom_margin=&#8221;|||&#8221; custom_padding=&#8221;54px|20px|60px|20px&#8221; animation_style=&#8221;zoom&#8221; animation_intensity_zoom=&#8221;10%&#8221; hover_enabled=&#8221;0&#8243; border_radii=&#8221;on|4px|4px|4px|4px&#8221; border_color_all=&#8221;#00aeef&#8221; border_width_top=&#8221;6px&#8221; border_color_top=&#8221;#221f72&#8243; box_shadow_style=&#8221;preset3&#8243; box_shadow_color=&#8221;rgba(34,56,101,0.12)&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<p>We partner with scientists to conduct their research via independent data collection, capture, and analysis.<\/p>\n<ul>\n<li style=\"text-align: left\">eRAP is a web-based interactive tool for data entry and reporting. Custom databases are rapidly developed for longitudinal single and multi-site studies.<\/li>\n<li style=\"text-align: left\">REDCap* is a secure web application for building and managing online surveys and databases. Track data manipulation, user activity, export procedures, scheduling, calendaring, and branching logic.<\/li>\n<li style=\"text-align: left\">Data Ark utilizes FAIR principles to provide regularly updated high-quality data sets for reusability in research.<\/li>\n<\/ul>\n<p>All applications are HIPAA compliant.<\/p>\n<p>*Please note that our current build of REDCap is not 21 CFR 11 compliant.<\/p>\n<p>[\/et_pb_blurb][\/et_pb_column][et_pb_column type=&#8221;1_4&#8243; _builder_version=&#8221;3.25&#8243; background_color_gradient_direction=&#8221;243deg&#8221; custom_padding=&#8221;|||&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_blurb admin_label=&#8221;MSDW&#8221; title=&#8221;Mount Sinai Data Warehouse&#8221; image=&#8221;https:\/\/labs.icahn.mssm.edu\/minervalab\/wp-content\/uploads\/sites\/342\/2021\/10\/msdw-1-150&#215;150.png&#8221; _builder_version=&#8221;4.9.0&#8243; header_level=&#8221;h2&#8243; header_font=&#8221;|600|||||||&#8221; header_text_color=&#8221;#221f72&#8243; 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