{"id":121004,"date":"2020-10-15T07:00:36","date_gmt":"2020-10-15T07:00:36","guid":{"rendered":"https:\/\/blogs.nvidia.com\/?p=47559"},"modified":"2020-10-15T07:00:36","modified_gmt":"2020-10-15T07:00:36","slug":"how-gpus-are-helping-paris-public-hospital-system-combat-the-spread-of-covid-19","status":"publish","type":"post","link":"https:\/\/webdomino.net\/index.php\/nvidia\/how-gpus-are-helping-paris-public-hospital-system-combat-the-spread-of-covid-19\/","title":{"rendered":"How GPUs Are Helping Paris\u2019 Public Hospital System Combat the Spread of COVID-19"},"content":{"rendered":"

In the battle against COVID-19, Greater Paris University Hospitals – Public Assistance Hospital of Paris (AP-HP is the French acronym) isn\u2019t just on the medical front lines \u2014 it\u2019s on the data front lines as well.<\/p>\n

With a network of 39 hospitals treating 8.3 million patients each year, AP-HP is a major actor in the fight against COVID-19.<\/p>\n

Along with its COVID-19 cases comes an awful lot of data, including now geodata that can potentially help lessen the impact of the pandemic. AP-HP, which partners with seven universities, already had the ability to analyze large amounts of medical data. It had previously created dashboards that combined cancer cases and geodata. So, it was logical to pursue and extend its role during the pandemic.<\/p>\n

The expected volume of COVID-19 data and geodata would probably have tested AP-HP\u2019s data crunching capacity. To mitigate this critical challenge, the hospital\u2019s information systems administrators turned to Kinetica<\/a>, a provider of streaming data warehouses and real-time analytics and a member of the NVIDIA Inception<\/a> program for AI startups.<\/p>\n

Kinetica\u2019s offering harnesses the power of NVIDIA GPUs to quickly convert case location data into usable intelligence. And in the fight against COVID-19, speed is everything.<\/p>\n

The project team also used NVIDIA RAPIDS<\/a> to speed up the machine learning algorithms integrated into the platform. RAPIDS accelerates analytics and data science pipelines on NVIDIA GPUs by taking advantage of GPU parallelism and high memory bandwidth.<\/p>\n

\u201cHaving the ability to perform this type of analysis in real time is really important during a pandemic,\u201d said Hector Countouris, the project lead at AP-HP. \u201cAnd more data is coming.\u201d<\/p>\n

Analyzing COVID Contact Data<\/b><\/h2>\n

What Countouris and his colleagues are most focused on is using COVID-related geodata to understand where virus \u201chot spots\u201d are and the dynamic of the outbreak. Looking for cluster locations can help decision-making at the district or region level.<\/p>\n

In addition, they\u2019re looking at new signals to improve early detection of COVID patients. This includes working with data from other regional agencies.<\/p>\n

If patients are diagnosed with COVID, they\u2019ll be asked by the relevant agencies via a phone call about their recent whereabouts and contacts to help with contact tracing. This is the first time that a wide range of data from different partners in the Paris area will be integrated to allow for contact tracing and timely alerts about a potential exposure. The result will be a newfound ability to see how clusters of COVID-19 cases evolve.<\/p>\n

\u201cWe hope that in the near future we will be able to follow how a cluster evolves in real time,\u201d said Countouris.<\/p>\n

The goal is to enable public health decision-makers to implement prevention and control measures and assess their effectiveness. The data can also be integrated with other demographic data to study the viral spread and its possible dependency on socio-economics and other factors.<\/p>\n

Attacking Bottlenecks with GPUs<\/b><\/h2>\n

Prior to engaging with Kinetica, such data-intensive projects involved so much time for loading the data that they couldn\u2019t be analyzed quickly enough to deliver real-time benefits.<\/p>\n

\u201cNow, I don\u2019t feel like I have a bottleneck,\u201d said Countouris. \u201cWe are continuously integrating data and delivering dashboards to decision makers within hours. And with robust real-time pipelines allowing for continuous data ingestion, we can now focus on building better dashboards.\u201d<\/p>\n

In the past, to get data in a specific and usable format, they would need to do a lot of pre-processing. With Kinetica\u2019s Streaming Data Warehouse powered by NVIDIA V100 Tensor Core GPUs, that\u2019s no longer the case. Users can access the much richer datasets they demand.<\/p>\n

Kinetica\u2019s platform is available on NVIDIA NGC<\/a>, a catalog of GPU-optimized AI containers that let enterprises quickly operationalize extreme analytics, machine learning and data visualization. This eliminates complexity and lets organizations deploy cloud, on-premises or hybrid models for optimal business operations.<\/p>\n

\u201cI don\u2019t think we could meet user expectations for geodata without GPU power,\u201d he said. \u201cThere is just too much data and geodata to provide for too many users at the same time.\u201d<\/p>\n

AP-HP\u2019s COVID-related work has already built a foundation upon which to do follow-up work related to emergency responses in general. The hospital information system\u2019s interest for that kind of data is far from over.<\/p>\n

\u201cThe fact that we helped the decision-making process and that officials are using our data is the measure of success,\u201d said Countouris. \u201cWe have a lot to do. This is only the beginning.\u201d<\/p>\n

Countouris presented the team\u2019s work<\/a> last week at the GPU Technology Conference<\/a>. Registered GTC attendees can view the talk on demand. It will be available for replay to the general public early next month.<\/p>\n

Kinetica will also be part of the NVIDIA Startup Village Booth at the HLTH conference<\/a>, presenting on Oct. 16 at 2 p.m. Pacific time.<\/p>\n<\/div>

The post How GPUs Are Helping Paris\u2019 Public Hospital System Combat the Spread of COVID-19<\/a> appeared first on The Official NVIDIA Blog<\/a>.<\/p>\n

\n<\/a> <\/a>\n<\/div>\"\"\/","protected":false},"excerpt":{"rendered":"

In the battle against COVID-19, Greater Paris University Hospitals – Public Assistance Hospital of Paris (AP-HP is the French acronym) isn’t just on the medical front lines — it’s on the data front lines as well. With a network of 39 hospitals treating 8.3 million patients each year, AP-HP is a major actor in the Read article ><\/a><\/p>\n

The post How GPUs Are Helping Paris’ Public Hospital System Combat the Spread of COVID-19<\/a> appeared first on The Official NVIDIA Blog<\/a>.<\/p>\n","protected":false},"author":300,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[343],"tags":[4223,2181,12671,7256,7017,13218],"yoast_head":"\nHow GPUs Are Helping Paris\u2019 Public Hospital System Combat the Spread of COVID-19 - WebDomino.NET<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/webdomino.net\/index.php\/nvidia\/how-gpus-are-helping-paris-public-hospital-system-combat-the-spread-of-covid-19\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How GPUs Are Helping Paris\u2019 Public Hospital System Combat the Spread of COVID-19 - WebDomino.NET\" \/>\n<meta property=\"og:description\" content=\"In the battle against COVID-19, Greater Paris University Hospitals – Public Assistance Hospital of Paris (AP-HP is the French acronym) isn’t just on the medical front lines — it’s on the data front lines as well. 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