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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