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GTC ON-DEMAND

Topic(s) Filter: Genomics & Bioinformatics
Presentation
Media
Abstract:
We'll discuss the computational challenge of aligning short DNA reads to very large reference genomes, a problem that tests the limits of computing hardware. We'll explain how adapting a CUDA-accelerated short-read aligner to handle these genomes r ...Read More
Abstract:
We'll discuss the computational challenge of aligning short DNA reads to very large reference genomes, a problem that tests the limits of computing hardware. We'll explain how adapting a CUDA-accelerated short-read aligner to handle these genomes resulted in a tenfold reduction in execution time.  Back
 
Topics:
Genomics & Bioinformatics, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9350
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Abstract:
We'll discuss how interpretable deep learning can significantly advance our understanding of genomic regulation. All our cells have the same DNA sequence, yet different cell-types express different genes in a process called genomic regulation. This ...Read More
Abstract:
We'll discuss how interpretable deep learning can significantly advance our understanding of genomic regulation. All our cells have the same DNA sequence, yet different cell-types express different genes in a process called genomic regulation. This regulation is driven by binding regulatory proteins to DNA. The vast majority of disease-associated mutations do not disrupt the DNA sequences of genes, but rather disrupt DNA sequences important for regulatory protein binding. Unfortunately, conventional computational models fail to explain which regulatory proteins are impacted for over 90 percent of such mutations. We show that by using deep learning coupled with our interpretation algorithms DeepLIFT (https://github.com/kundajelab/deeplift) and TF-MoDISco (https://github.com/kundajelab/tfmodisco) we can explain a substantially greater fraction of mutations that impact genomic regulation and obtain novel biological insights that are not provided by other methods.  Back
 
Topics:
Genomics & Bioinformatics, Deep Learning & AI Frameworks, Computational Biology & Chemistry
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9632
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Abstract:
We'll describe our work to develop multi-task deep learning models for the improved genetic risk prediction of coronary artery disease. Although studies have shown that basic coronary artery disease genetic-risk prediction models provide modest clin ...Read More
Abstract:
We'll describe our work to develop multi-task deep learning models for the improved genetic risk prediction of coronary artery disease. Although studies have shown that basic coronary artery disease genetic-risk prediction models provide modest clinical utility, improved comprehensive models can make this a reality of clinical practice. This information can help guide therapy decisions and provide an impetus for optimizing lifestyle modifications, thereby improving health outcomes and clinical efficiency. Some preliminary models have been described for autoencoding genetic data, but these models pay no attention to the underlying structure of genetic data. We'll talk about our work to provide best practices for autoencoding genetic data, with the ultimate goal of using these latent genetic factors as input for improved neural network and deep learning-based genetic risk prediction models.  Back
 
Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9663
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Abstract:
Learn about the importance of genomics in precision medicine and understand how researchers are decoding genomic information by building deep learning models. We'll show how the Kipoi model zoo for genomics (kipoi.org) can help in this endeavor and ...Read More
Abstract:
Learn about the importance of genomics in precision medicine and understand how researchers are decoding genomic information by building deep learning models. We'll show how the Kipoi model zoo for genomics (kipoi.org) can help in this endeavor and discuss several Kipoi use cases that demonstrate how it facilitates using, sharing, archiving, and building deep learning models in genomics. In addition, we'll highlight some recent successes of deep learning in genomics. Session participants can expect to gain appreciation for sharing end-to-end processing pipelines (not just models) and gain insight into how deep learning and GPU hardware accelerators are changing genomics.  Back
 
Topics:
Genomics & Bioinformatics, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9705
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Abstract:
Genes fused to one another can drive aggressive cancer cell growth. Fused MYB and NFIB genes are a hallmark of adenoid cystic carcinoma (ACC), but scientists don't yet know how the combined MYB-NFIB protein functions. Learn how we're working to bet ...Read More
Abstract:
Genes fused to one another can drive aggressive cancer cell growth. Fused MYB and NFIB genes are a hallmark of adenoid cystic carcinoma (ACC), but scientists don't yet know how the combined MYB-NFIB protein functions. Learn how we're working to better understand the complex biological interactions that lead to cancer. We'll describe how we investigated the MYB-NFIB fusion protein in ACC by ingesting many large, publicly available biological databases into a colossal hypergraph database designed to preserve the hierarchical structure and relationships inherent in biological data. We'll discuss how we implemented a supervised learning model to identify meaningful patterns that could explain ACC tumor biology. We will also cover how using GPUs results in a thousandfold increase in logistic regression analysis computational efficiency.  Back
 
Topics:
Genomics & Bioinformatics, AI in Healthcare, Accelerated Data Science
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9760
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Abstract:
We will discuss the scientific drivers for moving bioinformatics software to GPU platforms. The DOE Joint Genome Institute generates petabytes of environmental genomics data each year that is shared with thousands of scientists through web-based data ...Read More
Abstract:
We will discuss the scientific drivers for moving bioinformatics software to GPU platforms. The DOE Joint Genome Institute generates petabytes of environmental genomics data each year that is shared with thousands of scientists through web-based data analysis platforms. As sequencing technology changes, the character of the data changes and enables scientists to ask new questions that can be answered with higher fidelity. These data are integrated with the entire corpus of data generated by the DOE JGI, as well as labs around the world, leading to the need for large-scale high-performance computing that leverages the DOE Advanced Scientific Computing Research user facilities. We'll explain how systems like Summit at the Oak Ridge Leadership Computing Facility enable large-scale analysis of multi-omics data, which leads to new discoveries and new hypotheses.  Back
 
Topics:
Genomics & Bioinformatics, Accelerated Data Science
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9945
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Abstract:
在这个演讲题目中,我们会呈现现阶段大量科学计算领域利用深度学习、机器学习来加速各种高性能计算问题解决速度的案例。我们会讨论最新的技术进展和相应所带来的性能的提升。我们也会探讨现阶段在科学计算中应用 AI 的障碍和一些可能的解决方案。 ...Read More
Abstract:
在这个演讲题目中,我们会呈现现阶段大量科学计算领域利用深度学习、机器学习来加速各种高性能计算问题解决速度的案例。我们会讨论最新的技术进展和相应所带来的性能的提升。我们也会探讨现阶段在科学计算中应用 AI 的障碍和一些可能的解决方案。  Back
 
Topics:
Genomics & Bioinformatics, HPC and AI
Type:
Talk
Event:
GTC China
Year:
2018
Session ID:
CH8407
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Abstract:
Oxford Nanopore has built the first and only real-time, portable DNA sequencer - the MinION. It is being used to bring DNA information to researchers in many sectors, including biomedical/cancer research, environmental monitoring, agriculture, f ...Read More
Abstract:

Oxford Nanopore has built the first and only real-time, portable DNA sequencer - the MinION. It is being used to bring DNA information to researchers in many sectors, including biomedical/cancer research, environmental monitoring, agriculture, food/ water testing, and education. Oxford Nanopore is using GPUs to make sure that genomic data can be processed in real time, delivering potential benefits of rapid insights to users in any environment. Leila Luheshi and Rosemary Dokos will talk about current and potential healthcare applications of Nanopore technology, and how GPUs will turn sequence data into rapid insights for disease or environmental management.

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Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8179
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Abstract:
The MULTI-X platform simplifies the logistical challenges of deploying AI and ML solutions by providing pre-configured environments with ad-hoc scalable computing resources to quickly build, test, share and reproduce scientific applications. Its ...Read More
Abstract:

The MULTI-X platform simplifies the logistical challenges of deploying AI and ML solutions by providing pre-configured environments with ad-hoc scalable computing resources to quickly build, test, share and reproduce scientific applications. Its comprehensible modular framework accelerates the development and reduces the burden and cost of implementing AI solutions. The talk will include details of two exemplary deployments in the area of Cardiac Image Analysis, presented together with the outcome of the analysis of 5000 subjects of the UK-Biobank database. Developing and deploying AI solutions for clinical research use cases can be complex, resource intensive, and therefore expensive and challenging to implement for many researchers, groups and healthcare organisations. In the era of Big-Data and the IoT, the most critical problems are related to the secure access and management of large heterogeneous datasets, the deployment of GPU-accelerated massive parallel processing systems, and the setup of development environments encompassing complex ML tools and applications. Two exemplary use cases of the implementation of GPU-enabled AI solutions in the area of Cardiac Image Analysis, both developed and deployed in MULTI-X, will be presented together with the outcome of the analysis of 5000 Subjects of the UK-Biobank database.

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Topics:
Genomics & Bioinformatics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8274
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Speakers:
, ,
Abstract:
Learn about the newest advancements in brain reading and neuroprosthetics, made possible by deep learning techniques, experimentation and augmented reality. Brain reading enables us to observe what people are seeing and perceiving just by analys ...Read More
Abstract:

Learn about the newest advancements in brain reading and neuroprosthetics, made possible by deep learning techniques, experimentation and augmented reality. Brain reading enables us to observe what people are seeing and perceiving just by analysing their 3D brain scans, recorded while subjects are observing things in an MRI scanner. Brain writing is, to an extent, opposite, performed by direct stimulation of the brain via microelectrode arrays with the aim of inducing percepts. In developing a new generation of cortical neuroprostheses to stimulate the visual cortex, we are now working toward restoring meaningful visual perception in blind people.

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Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8375
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Speakers:
,
Abstract:
A Norwegian oil company needed to fix 1 million images of seabed, taken with artificial light, to be able to create a geological orthophoto. Due to light absorption in the water, all images were bright in center and dark at the sides. The poor q ...Read More
Abstract:

A Norwegian oil company needed to fix 1 million images of seabed, taken with artificial light, to be able to create a geological orthophoto. Due to light absorption in the water, all images were bright in center and dark at the sides. The poor quality of these images stopped us from machine analysis, so we used NVIDIA CUDA to create a routine that automatically analyzed all images one by one and fixed the inconsistent lighting. Afterwards, the images could be analysed with machine learning. The routine analysed every image separately and repaired them automatically.

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Topics:
Artificial Intelligence and Deep Learning, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8148
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Speakers:
,
Abstract:
In this talk we will give an overview of the benefits GPU computing can provide to the Structural Bioinformatics field. We will explain how most of biomolecular simulations methods can be efficiently accelerated using massively computational arc ...Read More
Abstract:

In this talk we will give an overview of the benefits GPU computing can provide to the Structural Bioinformatics field. We will explain how most of biomolecular simulations methods can be efficiently accelerated using massively computational architectures and will show several fundamental research and technology transfer success cases.

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Topics:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8287
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Speakers:
,
Abstract:
We believe that medicine will be more precise and affordable. Physicians will integrate relevant patient data and insights at the point of decision for precise diagnostics. Therapy will be tailored to the characteristics of both the patient and ...Read More
Abstract:

We believe that medicine will be more precise and affordable. Physicians will integrate relevant patient data and insights at the point of decision for precise diagnostics. Therapy will be tailored to the characteristics of both the patient and disease ? resulting in the right treatment for the right patient at the right time. AI-powered decision support could help to balance the need for personalization when it matters and standardization to reduce unwarranted variations.

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Topics:
Medical Imaging & Radiology, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8290
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Speakers:
, , ,
Abstract:
This session will feature at the Women at GTC Lunch event and will explore the topic of "Leadership In The Age of AI". All attendees who support diversity and inclusion in the tech world are welcome to join.
 
Topics:
AI & Deep Learning Business Track (High Level), Artificial Intelligence and Deep Learning, Autonomous Vehicles, Virtual Reality & Augmented Reality, Genomics & Bioinformatics
Type:
Panel
Event:
GTC Europe
Year:
2018
Session ID:
E8497
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Abstract:
It is not always easy to accelerate a complex serial algorithm with CUDA parallelization. A case in point is that of aligning bisulfite-treated DNA (bsDNA) sequences to a reference genome. A simple CUDA adaptation of a CPU-based implementation c ...Read More
Abstract:

It is not always easy to accelerate a complex serial algorithm with CUDA parallelization. A case in point is that of aligning bisulfite-treated DNA (bsDNA) sequences to a reference genome. A simple CUDA adaptation of a CPU-based implementation can improve the speed of this particular kind of sequence alignment, but it's possible to achieve order-of-magnitude improvements in throughput by organizing the implementation so as to ensure that the most compute-intensive parts of the algorithm execute on GPU threads.

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8130
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Abstract:
We'll disscuss how GPUs are playing a central role in making advances in Ion Torrent's targeted sequencing workflow and talk about the S5 DNA sequencer from Ion Torrent that is enabling democratization of sequencing market and accel ...Read More
Abstract:

We'll disscuss how GPUs are playing a central role in making advances in Ion Torrent's targeted sequencing workflow and talk about the S5 DNA sequencer from Ion Torrent that is enabling democratization of sequencing market and accelerating research in precision medicine at a breathtaking pace with the help of GPUs. We'll highlight our work in liquid biopsy and non-invasive prenatal testing and how the breadth in technology offerings in semiconductor chips gives us the scale of sequencing from small panels to exomes. We'll discuss our analysis pipeline and the latest and greatest in algorithm development and acceleration on GPUs as well as our experiences ranging from Fermi to Pascal GPU architectures. 

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8419
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Abstract:
Attendees will learn how GPU computing significantly increases accuracy of predictions in solving one of the hardest structural bioinformatics problem -- protein-protein complexes prediction (docking). We will present how it is used in modern drug di ...Read More
Abstract:
Attendees will learn how GPU computing significantly increases accuracy of predictions in solving one of the hardest structural bioinformatics problem -- protein-protein complexes prediction (docking). We will present how it is used in modern drug discovery by Russian biotechnology company BIOCAD. Protein-protein docking appears on a number of steps in modern drug discovery, so it is essential to make accurate predictions to design more quality drugs. It is a very computationally intensive task due to large solution space and big sizes of protein molecular systems. GPU computing makes it possible to scan huge solution space by solid metric of Gibbs Free Energy, thereby, significantly improving the quality of predictions as well as decreases overall calculation time.  Back
 
Topics:
Computational Biology & Chemistry, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8226
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Abstract:
We'll present how to apply deep learning to predict small-sized protein complexes with multiple biological information and hybrid deep learning model. We'll describe the background of the problem, what kind of biological information are u ...Read More
Abstract:
We'll present how to apply deep learning to predict small-sized protein complexes with multiple biological information and hybrid deep learning model. We'll describe the background of the problem, what kind of biological information are useful for accurately predicting small-sized protein complexes, how to improve the prediction accuracy by using hybrid deep learning models for different information, and compare the performance of multiple deep learning models for this problem.  Back
 
Topics:
Computational Biology & Chemistry, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8333
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Abstract:
Deep learning models give state-of-the-art results on diverse problems, but their lack of interpretability is a major problem. Consider a model trained to predict which DNA mutations cause disease: if the model performs well, it has likely ident ...Read More
Abstract:

Deep learning models give state-of-the-art results on diverse problems, but their lack of interpretability is a major problem. Consider a model trained to predict which DNA mutations cause disease: if the model performs well, it has likely identified patterns that biologists would like to understand. However, this is difficult if the model is a black box. We present algorithms that provide detailed explanations for individual predictions made by a deep learning model and discover recurring patterns across the entire dataset. Our algorithms address significant limitations of existing interpretability methods. We show examples from genomics where the use of deep learning in conjunction with our interpretability algorithms leads to novel biological insights.

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8907
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Abstract:
Protecting crew health is a critical concern for NASA in preparation of long duration, deep-space missions like Mars. Spaceflight is known to affect immune cells. Splenic B-cells decrease during spaceflight and in ground-based physiological mode ...Read More
Abstract:

Protecting crew health is a critical concern for NASA in preparation of long duration, deep-space missions like Mars. Spaceflight is known to affect immune cells. Splenic B-cells decrease during spaceflight and in ground-based physiological models. The key technical innovation presented by our work is end-to-end computation on the GPU with the GPU Data Frame (GDF), running on the DGXStation, to accelerate the integration of immunoglobulin gene-segments, junctional regions, and modifications that contribute to cellular specificity and diversity. Study results are applicable to understanding processes that induce immunosuppressionlike cancer therapy, AIDS, and stressful environments here on earth.

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Topics:
AI in Healthcare, Performance Optimization, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8528
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Abstract:
The NVIDIA Genomics Group has developed a deep learning platform to transform noisy, low-quality DNA sequencing data into clean, high-quality data. Hundreds of DNA sequencing protocols are used to profile phenomena such as protein-DNA binding an ...Read More
Abstract:

The NVIDIA Genomics Group has developed a deep learning platform to transform noisy, low-quality DNA sequencing data into clean, high-quality data. Hundreds of DNA sequencing protocols are used to profile phenomena such as protein-DNA binding and DNA accessibility. For example, the ATAC-seq protocol identifies open genomic sites by sequencing open DNA fragments; genome-wide fragment counts provide a profile of DNA accessibility. Recent advances enable profiling from smaller patient samples than previously possible. To reduce sequencing cost, we developed a convolutional neural network that denoises data from a small number of DNA fragments, making the data suitable for various downstream tasks. Our platform aims to accelerate adoption of DNA sequencers by minimizing data requirements.

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8602
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Abstract:
Nanopore sequencing is a breakthrough technology that marries cutting edge semiconductor processes together with biochemistry, achieving fast, scalable, single molecule DNA sequencing. The challenge is real-time processing of gigabytes of data p ...Read More
Abstract:

Nanopore sequencing is a breakthrough technology that marries cutting edge semiconductor processes together with biochemistry, achieving fast, scalable, single molecule DNA sequencing. The challenge is real-time processing of gigabytes of data per second in a compact benchtop instrument. GPUDirect, together with the cuDNN library, enables Roche to maximize the effectiveness of Tesla V100 GPUs in their next generation sequencing instrument. Attendees will learn how these pieces come together to build a streaming AI inference engine to solve a signal processing workflow. Analysis and performance comparisons of the new TensorCore units, available on Volta hardware, will be included.cal cuDNN API

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8947
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Abstract:
We will demonstrate the features and capabilities of OpenACC for porting and optimizing the ParDOCK docking module of the Sanjeevini suite for computer aided drug discovery developed at the HPC and Supercomputing Facility for Bioinformatics and Compu ...Read More
Abstract:
We will demonstrate the features and capabilities of OpenACC for porting and optimizing the ParDOCK docking module of the Sanjeevini suite for computer aided drug discovery developed at the HPC and Supercomputing Facility for Bioinformatics and Computational Biology at the Indian Institute of Technology Delhi. We have used OpenACC to efficiently port the existing C++ programming model of ParDOCK software with minimal code modifications to run on latest NVIDIA P100 GPU card. These code modifications and tuning resulted in a six times average speedup of improvements in turnaround time. By implementing openACC, the code is now able to sample ten times more ligand conformations leading to an increase in accuracy. The ACC ported ParDOCK code is now able to predict a correct pose of a protein-ligand interaction from 96.8 percent times, compared to 94.3 percent earlier (for poses under 1 A) and 89.9 percent times compared to 86.7 percent earlier (for poses under 0.5 A).  Back
 
Topics:
Computational Biology & Chemistry, Performance Optimization, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8188
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