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The need of an Accelerator Operating System

InAccel FPGA orchestrator abstracts away the available FPGA resources serving as an OS layer and “kubernetes-alike” layer for the applications that need to be deployed on FPGAs. The main advantages that InAccel’s orchestrator offers are easy deployment, automated resource management and instant scaling

Data scientists, ML engineers and HPC users can now speedup their applications using the power of FPGAs from their browser. InAccel has made available as a demo a framework that allow any user to instantly log in in the platform and start accessing the Xilinx Vitis™ libraries on a cluster of Alveo™ cards. The framework is built on top of Jupyter Hub.

InAccel FPGA Operator: Simplifying FPGA management in Kubernetes

Helm is a package manager for Kubernetes that allows developers and operators to more easily package, configure, and deploy applications and services onto Kubernetes clusters. The InAccel FPGA Operator is a Helm chart deployed, cloud-native method to standardize and automate the deployment of all necessary components for provisioning FPGA-enabled Kubernetes systems.

FPGA integration easier than ever

InAccel has developed a unique FPGA orchestrator that allows easy deployment, instant scaling and dynamic resource management of the FPGA clusters. InAccel’s FPGA orchestrator allows the deployment of FPGAs as a Platform ready to be used by the software developers just like any other computing system. InAccel FPGA orchestrator abstracts away the available FPGA resources serving as an OS layer and “kubernetes-alike” layer for the applications that need to be deployed on FPGAs allowing easy integration with any framework.

What FPGAs can learn from the CPU and the GPU world: Automatic deployment, scaling and dynamic resource management

Accelerate ML workflows with Kubeflow using InAccel FPGA orchestrator

In this article we show how Kubeflow can be used to perform a design space exploration and hyper parameter tuning faster using Kubeflow and utilizing the power of FPGAs.

FPGA deployment and scaling on distributed systems; the missing layer

, InAccel developed world-first FPGA orchestrator that allows easy deployment, instant scaling and seamless resource management of the FPGA clusters. InAccel’s FPGA orchestrator allows the deployment of FPGAs as a Platform ready to be used by the software developers just like any other computing system. InAccel FPGA orchestrator abstracts away the available FPGA resources serving as an OS layer and “kubernetes-alike” layer for the applications that need to be deployed on FPGAs.

Run 100x faster your Scikit-learn machine learning applications using FPGAs: A use case on Naive Bayes

Check how you can speedup your Scikit learn applications by more than 100x using FPGAs and with zero code changes.

How to make FPGA deployment in data centers as easy as any computing resource

, InAccel developed the unique FPGA orchestrator that allows easy deployment, instant scaling and seamless resource management of the FPGA clusters. InAccel’s FPGA orchestrator allows the deployment of FPGAs as a Platform ready to be used by the software developers just like any other computing system. At the same time, InAccel’s orchestrator integrated with InAccel’s FPGA repository allows the utilization of FPGAs as a service using off-the-shelf ready to use accelerators.

Multi-tenant, enterprise-grade FPGA cluster deployment using Kubesphere console

Kubernetes on FPGA using Kubesphere extends the industry standard container orchestration platform with FPGA acceleration capabilities. With first class support for FPGA resources scheduling, developers and DevOps engineers can now build, deploy, orchestrate and monitor FPGA-accelerated application deployments on heterogeneous, multi-cloud clusters.

How FPGAs can prevail as the next computing platform

One of the main issues raised by many participants and speakers was the need for an OS layers for the widespread adoption of FPGAs that will allow easy deployment, instant scaling and seamless sharing of the FPGA resources. An abstraction layer that will allow software developers to utilize FPGAs without prior knowledge of FPGA can accelerate the adoption of FPGAs in many applications.

Making FPGAs deployment as easy as processors

CPU, GPU or FPGA: Performance evaluation of cloud computing platforms for Machine Learning training

FPGAs on the cloud (f1.2xlarge on this case with InAccel ML suite) achieves the best combination in terms of performance-accuracy and cost.

Deploying FPGAs from Git repos instantly using BinderHub

Connecting 2 worlds: Bringing the benefits of accelerators to the software community, instantly

Speedup your applications with zero code changes: The seamless way to make FPGA accessible to the software community

Accelerating data science and HPC applications with FPGAs using Jupyter Hub, instantly

InAccel, a world-leader in application acceleration through the use of adaptive acceleration platforms (ACAP, FPGA) has integrated JupyterHub in its technology. InAccel provides an FPGA resource manager that allows the instant deployment, scaling and virtualization of FPGAs making easier than ever the utilization of FPGA clusters for applications like machine learning, data processing, data analytics and many more HPC workloads.

Accelerating Spark ML over SQL Server 2019 Big Data Cluster, instantly

Automated deployment, scaling and management of FPGA clusters: the easy way

Coral is a scalable, reliable and fault-tolerant distributed acceleration system responsible for monitoring, virtualizing and orchestrating clusters of FPGAs. Coral also introduces high-level abstractions by exposing FPGAs as a single pool of accelerators to any application developer that she can easily invoke through simple API calls. Finally, Coral runs as a microservice and is able to run on top of other state-of-the-art resource managers like Hadoop YARN and Kubernetes.

InAccel’s Accelerated ML suite boosts Spark ML as much as 7x using Intel’s® Arria® FPGAs

The IP cores for logistic regression and K-means clustering leverage the processing power of the Intel FPGAs to speedup the training of these algorithms. The IP core is optimized for the Intel® FPGAs (e.g. Arria® 10) available as instances on Alibaba cloud.