�ݺ�ߣshows by User: kachris

�ݺ�ߣshows by User: kachris / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: kachris / Thu, 02 Sep 2021 11:37:49 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: kachris InAccel FPGA Operator for instant Cloud deployment /slideshow/inaccel-fpga-operator-for-instant-cloud-deployment/250102342 202109fplsponsor-210902113750
The InAccel FPGA operator manages FPGA resources in a Kubernetes cluster and automates tasks related to bootstrapping FPGA nodes. Since the FPGA is a special resource in the cluster, it requires a few components to be installed before application workloads can be deployed onto the FPGA. These components include the FPGA drivers, Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more. A Helm chart is provided for easily deploying the FPGA operator in a cluster to provision the InAccel software on FPGA-enabled nodes. ]]>
The InAccel FPGA operator manages FPGA resources in a Kubernetes cluster and automates tasks related to bootstrapping FPGA nodes. Since the FPGA is a special resource in the cluster, it requires a few components to be installed before application workloads can be deployed onto the FPGA. These components include the FPGA drivers, Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more. A Helm chart is provided for easily deploying the FPGA operator in a cluster to provision the InAccel software on FPGA-enabled nodes. ]]> Thu, 02 Sep 2021 11:37:49 GMT /slideshow/inaccel-fpga-operator-for-instant-cloud-deployment/250102342 kachris@slideshare.net(kachris) InAccel FPGA Operator for instant Cloud deployment kachris The InAccel FPGA operator manages FPGA resources in a Kubernetes cluster and automates tasks related to bootstrapping FPGA nodes. Since the FPGA is a special resource in the cluster, it requires a few components to be installed before application workloads can be deployed onto the FPGA. These components include the FPGA drivers, Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more. A Helm chart is provided for easily deploying the FPGA operator in a cluster to provision the InAccel software on FPGA-enabled nodes. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/202109fplsponsor-210902113750-thumbnail.jpg?width=120&height=120&fit=bounds" /> The InAccel FPGA operator manages FPGA resources in a Kubernetes cluster and automates tasks related to bootstrapping FPGA nodes. Since the FPGA is a special resource in the cluster, it requires a few components to be installed before application workloads can be deployed onto the FPGA. These components include the FPGA drivers, Kubernetes device plugin, container runtime and others such as automatic node labelling, monitoring and more. A Helm chart is provided for easily deploying the FPGA operator in a cluster to provision the InAccel software on FPGA-enabled nodes.

InAccel FPGA Operator for instant Cloud deployment from Christoforos Kachris

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0 Instant scaling and deployment of Vitis Libraries on Alveo clusters using InAccel Resource manager /kachris/instant-scaling-and-deployment-of-vitis-libraries-on-alveo-clusters-using-inaccel-resource-manager 202006inaccelxilinxwebinar-200603081357
In this webinar we will show how to address the 3 main challenges in the domain of FPGA deployment. First, we will show you how you can deploy your applications from high level frameworks like python, java scikit-learn and Keras easier than ever. Then, we will show how you can scale out your applications from frameworks like Keras and Scikit Learn on multiple FPGA Alveo cards automatically. Finally, we will show you how multiple users can share the available FPGA resources seamlessly. We will show how InAccel allows dynamic resource management of the FPGA resources in order to allow multi application and multi tenant deployment. ]]>
In this webinar we will show how to address the 3 main challenges in the domain of FPGA deployment. First, we will show you how you can deploy your applications from high level frameworks like python, java scikit-learn and Keras easier than ever. Then, we will show how you can scale out your applications from frameworks like Keras and Scikit Learn on multiple FPGA Alveo cards automatically. Finally, we will show you how multiple users can share the available FPGA resources seamlessly. We will show how InAccel allows dynamic resource management of the FPGA resources in order to allow multi application and multi tenant deployment. ]]> Wed, 03 Jun 2020 08:13:57 GMT /kachris/instant-scaling-and-deployment-of-vitis-libraries-on-alveo-clusters-using-inaccel-resource-manager kachris@slideshare.net(kachris) Instant scaling and deployment of Vitis Libraries on Alveo clusters using InAccel Resource manager kachris In this webinar we will show how to address the 3 main challenges in the domain of FPGA deployment. First, we will show you how you can deploy your applications from high level frameworks like python, java scikit-learn and Keras easier than ever. Then, we will show how you can scale out your applications from frameworks like Keras and Scikit Learn on multiple FPGA Alveo cards automatically. Finally, we will show you how multiple users can share the available FPGA resources seamlessly. We will show how InAccel allows dynamic resource management of the FPGA resources in order to allow multi application and multi tenant deployment. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/202006inaccelxilinxwebinar-200603081357-thumbnail.jpg?width=120&height=120&fit=bounds" /> In this webinar we will show how to address the 3 main challenges in the domain of FPGA deployment. First, we will show you how you can deploy your applications from high level frameworks like python, java scikit-learn and Keras easier than ever. Then, we will show how you can scale out your applications from frameworks like Keras and Scikit Learn on multiple FPGA Alveo cards automatically. Finally, we will show you how multiple users can share the available FPGA resources seamlessly. We will show how InAccel allows dynamic resource management of the FPGA resources in order to allow multi application and multi tenant deployment.

Instant scaling and deployment of Vitis Libraries on Alveo clusters using InAccel Resource manager from Christoforos Kachris

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0 InAccel FPGA resource manager and orchestrator /slideshow/inaccel-fpga-resource-manager-and-orchestrator/170518580 inaccelfpgamngtutorial-190910081455
Use InAccel's FPGA resource manager to automatically deploy, scale, virtualize and manage FPGA clusters on cloud or on-prem instantly with zero overhead. ]]>
Use InAccel's FPGA resource manager to automatically deploy, scale, virtualize and manage FPGA clusters on cloud or on-prem instantly with zero overhead. ]]> Tue, 10 Sep 2019 08:14:55 GMT /slideshow/inaccel-fpga-resource-manager-and-orchestrator/170518580 kachris@slideshare.net(kachris) InAccel FPGA resource manager and orchestrator kachris Use InAccel's FPGA resource manager to automatically deploy, scale, virtualize and manage FPGA clusters on cloud or on-prem instantly with zero overhead. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/inaccelfpgamngtutorial-190910081455-thumbnail.jpg?width=120&height=120&fit=bounds" /> Use InAccel's FPGA resource manager to automatically deploy, scale, virtualize and manage FPGA clusters on cloud or on-prem instantly with zero overhead.

InAccel FPGA resource manager and orchestrator from Christoforos Kachris

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0 InAccel FPGA resource manager /kachris/inaccel-fpga-resource-manager-157796949 inaccelfpgamng-190725103308
Coral is a framework that allows the distributed acceleration of large data sets across clusters of FPGA resources using simple programming models. It is designed to scale up from single devices to multiple FPGAs, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of FPGAs, each of which may be prone to failures. Coral abstracts FPGA resources (device, memory), enabling fault-tolerant heterogeneous distributed systems to easily be built and run effectively. It allows: - instant scalability to multiple FPGAs - seamless virtualization of the FPGA cluster]]>
Coral is a framework that allows the distributed acceleration of large data sets across clusters of FPGA resources using simple programming models. It is designed to scale up from single devices to multiple FPGAs, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of FPGAs, each of which may be prone to failures. Coral abstracts FPGA resources (device, memory), enabling fault-tolerant heterogeneous distributed systems to easily be built and run effectively. It allows: - instant scalability to multiple FPGAs - seamless virtualization of the FPGA cluster]]> Thu, 25 Jul 2019 10:33:08 GMT /kachris/inaccel-fpga-resource-manager-157796949 kachris@slideshare.net(kachris) InAccel FPGA resource manager kachris Coral is a framework that allows the distributed acceleration of large data sets across clusters of FPGA resources using simple programming models. It is designed to scale up from single devices to multiple FPGAs, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of FPGAs, each of which may be prone to failures. Coral abstracts FPGA resources (device, memory), enabling fault-tolerant heterogeneous distributed systems to easily be built and run effectively. It allows: - instant scalability to multiple FPGAs - seamless virtualization of the FPGA cluster <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/inaccelfpgamng-190725103308-thumbnail.jpg?width=120&height=120&fit=bounds" /> Coral is a framework that allows the distributed acceleration of large data sets across clusters of FPGA resources using simple programming models. It is designed to scale up from single devices to multiple FPGAs, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of FPGAs, each of which may be prone to failures. Coral abstracts FPGA resources (device, memory), enabling fault-tolerant heterogeneous distributed systems to easily be built and run effectively. It allows: - instant scalability to multiple FPGAs - seamless virtualization of the FPGA cluster

InAccel FPGA resource manager from Christoforos Kachris

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0 FPGA Acceleration of Apache Spark on AWS /slideshow/fpga-acceleration-of-apache-spark-on-aws/122293986 201809xdfinaccel-181107151234
This presentation gives an overview of InAccel's Accelerated Machine Learning Suite that allows to speedup ML applications on the cloud without changing your code. The Accelerated ML suite is fully compatible with Apache Spark and allows the seamless utilization of FPGA in AWS in order to speedup your applications. More at https://www.inaccel.com/]]>
This presentation gives an overview of InAccel's Accelerated Machine Learning Suite that allows to speedup ML applications on the cloud without changing your code. The Accelerated ML suite is fully compatible with Apache Spark and allows the seamless utilization of FPGA in AWS in order to speedup your applications. More at https://www.inaccel.com/]]> Wed, 07 Nov 2018 15:12:34 GMT /slideshow/fpga-acceleration-of-apache-spark-on-aws/122293986 kachris@slideshare.net(kachris) FPGA Acceleration of Apache Spark on AWS kachris This presentation gives an overview of InAccel's Accelerated Machine Learning Suite that allows to speedup ML applications on the cloud without changing your code. The Accelerated ML suite is fully compatible with Apache Spark and allows the seamless utilization of FPGA in AWS in order to speedup your applications. More at https://www.inaccel.com/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/201809xdfinaccel-181107151234-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation gives an overview of InAccel's Accelerated Machine Learning Suite that allows to speedup ML applications on the cloud without changing your code. The Accelerated ML suite is fully compatible with Apache Spark and allows the seamless utilization of FPGA in AWS in order to speedup your applications. More at https://www.inaccel.com/

FPGA Acceleration of Apache Spark on AWS from Christoforos Kachris

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0 https://cdn.slidesharecdn.com/profile-photo-kachris-48x48.jpg?cb=1648120538 https://cdn.slidesharecdn.com/ss_thumbnails/202109fplsponsor-210902113750-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/inaccel-fpga-operator-for-instant-cloud-deployment/250102342 InAccel FPGA Operator ... https://cdn.slidesharecdn.com/ss_thumbnails/202006inaccelxilinxwebinar-200603081357-thumbnail.jpg?width=320&height=320&fit=bounds kachris/instant-scaling-and-deployment-of-vitis-libraries-on-alveo-clusters-using-inaccel-resource-manager Instant scaling and de... https://cdn.slidesharecdn.com/ss_thumbnails/inaccelfpgamngtutorial-190910081455-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/inaccel-fpga-resource-manager-and-orchestrator/170518580 InAccel FPGA resource ...