Data researchers and Machine Learning designers can now speed up. It is possible by more than 10x computationally. That is concentrated remaining burdens. It declines the entire expense of possession with zero code changes. It completely underpins. It generally used structures. These are like Keras, Scikit-learn, Jupyter Notebooks, and Spark.
FPGAs are flexible hardware platforms. That can offer great performance, low-latency. It reduced OpEx for software. Examples are such as machine learning, video processing. It also adds quantitative finance, genomics, etc. However, the simple and efficient deployment are from users. That is, with no previous knowledge of FPGA has been hard.
InAccel is a pioneer in FPGA-based stride. That has released a hastened machine learning platform. It allows an instant dispatch of Machine Learning programs and neural network models.
InAccel provides an FPGA resource manager. It permits instant deployment, scaling. Also, source management of FPGAs is producing easier than ever the use of FPGAs. That is for applications. Examples are such as machine learning and data processing software. Users can deploy their software. It can be deployed from Python, Jupyter notebooks. Or even terminals can instantly deploy.
It goes throughout the JupyterHub integration. Users can now enjoy all the benefits. That JupyterHub provides, such as easy access. That is to the computational atmosphere. It is for the immediate execution of Jupyter journals. Together, clients would now be able to appreciate it. They will value the benefits of FPGAs. These are lower-latency, lower fulfillment time. Also, much higher usage is possible with no prior-knowledge of all FPGAs. InAccel’s frame allows the use of some other 3rd party IP cores. It is for machine learning, data analytics. This also adds genomics, compression, security. Computer vision applications are also covered.
InAccel’s FPGA orchestrator provides the Advanced Machine Learning Platform. It may be used on-prem. Or, It can be used on the cloud using the AWS f1 instances. This way, users can delight in the ease of the Jupyter notebooks. At the same time, experience vital speedups in their applications. That is like regression, clustering, or grading.
About InAccel, Inc.
InAccel helps businesses to speed up their software by using elastic hardware accelerators. It provides an unusual framework for seamless. It is the use of hardware accelerators from high tech frameworks like Spark and Jupyter. InAccel also develops high-performance accelerators. That is for applications like machine learning, compression, and data analytics.
