Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Due to its simplicity it has gained wide popularity among the data scientists and the HPC users that want to create and share applications that integrates the code, the comments and the results of the application.
JupyterHub brings the power of notebooks to groups of users. It gives users access to computational environments and resources without burdening the users with installation and maintenance tasks. Users - including students, researchers, and data scientists - can get their work done in their own workspaces on shared resources which can be managed efficiently by system administrators.
JupyterHub runs in the cloud or on your own hardware and makes it possible to serve a pre-configured data science environment to any user in the world. It is customizable and scalable, and is suitable for small and large teams, academic courses, and large-scale infrastructure.
BinderHub enables an end user to easily specify a desired computing environment from a Git repo. BinderHub then serves the custom computing environment at a URL which users can access remotely. BinderHub uses a JupyterHub running on Kubernetes for much of its functionality. Using BinderHub it’s easier than ever to execute an application hosted on a git repository to a computing platform.
FPGA deployment from Binderhub using InAccel FPGA manager
InAccel, a world-leader in application acceleration through the use of adaptive acceleration platforms (ACAP, FPGA) has integrated BinderHub 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.
Through the BinderHub integration, users can now enjoy all the benefits that BinderHub provides such as easy access to computational environment from a Git repository and instant execution of Jupyter notebooks. At the same time, users can now enjoy the benefits of FPGAs such as lower-latency, lower execution time and much higher performance without any prior-knowledge of FPGAs. InAccel’s framework allows the easy instantiation and deployment of Xilinx’s new Vitis Open-Source optimized libraries or 3rd party IP cores (for machine learning, data analytics, genomics, compression, encryption and computer vision applications.)
BinderHub using InAccel’s FPGA orchestrator can be used either on-prem (e.g. supporting the powerful Xilinx Alveo card) or on the cloud (e.g. AWS, Azure, Tencent, and Alibaba). That way, users can enjoy the simplicity of the BinderHub over Jupyter notebooks and at the same time experience significant speedups on their applications.
InAccel would like to thank the Xilinx CTO organization for their collaboration in support on this initiative.
More info at www.inaccel.com