TensorFlow Now Supports Fortran- Google’s open source machine learning framework is now compatible with the Fortran programming language.
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We’re excited to announce that TensorFlow now supports Fortran!
Fortran is a programming language that has been used for scientific and numeric computing for decades. It is known for its performance and efficiency, making it a good choice for machine learning applications.
With this release, TensorFlow now supports all major programming languages, making it easier than ever to develop machine learning applications.
What is TensorFlow?
TensorFlow is a powerful open-source software library for data analysis and machine learning. Originally developed by Google Brain team members for internal use, TensorFlow is now available to everyone under the Apache 2.0 open source license. TensorFlow supports a wide variety of platforms, including CPUs, GPUs, and TPUs, and has been used in a variety of applications such as image classification, natural language processing, and time series analysis.
What is Fortran?
Fortran is a general purpose programming language that is commonly used for scientific and engineering applications. It is particularly suited for high performance computing, and many numerical libraries are written in Fortran. TensorFlow is a popular open source machine learning library that supports a wide variety of programming languages, and it has now added support for Fortran. This means that users can now write TensorFlow programs in Fortran, making it easier to use TensorFlow with existing Fortran codebases.
Why is TensorFlow Now Supporting Fortran?
TensorFlow, the popular open-source machine learning platform, has announced support for the Fortran programming language. This move is aimed at making TensorFlow more accessible to scientists and engineers who are already familiar with Fortran.
Fortran is a long-established programming language that is particularly popular in scientific and engineering circles. It is known for its efficiency and is often used for high-performance computing tasks.
The addition of Fortran support to TensorFlow should make it easier for scientists and engineers to use the platform for their own projects. In particular, it should make it easier to interface TensorFlow with existing Fortran codebases.
TensorFlow is already a powerful tool for machine learning, and the addition of Fortran support will only make it more accessible and useful for those in the scientific and engineering communities.
What are the Benefits of TensorFlow Supporting Fortran?
TensorFlow, the popular open source machine learning library, now supports the Fortran programming language. This is significant news for the scientific and engineering community because Fortran is a high performance computing language that is used extensively in those domains.
The benefits of TensorFlow supporting Fortran are numerous. First, it allows scientific and engineering organizations to use TensorFlow with their existing Fortran codebases. Second, it makes it easier to integrate TensorFlow into existing high performance computing environments. Third, it allows TensorFlow to take advantage of the latest compilers and libraries that support Fortran.
This is a significant development for the TensorFlow community and will help to make TensorFlow even more popular in the scientific and engineering communities.
How Does TensorFlow Support Fortran?
TensorFlow has announced that it now supports the Fortran programming language. This is a significant development, as Fortran is a key language for scientific and numerical computing. TensorFlow is an open-source machine learning platform that is widely used in both academia and industry. The addition of Fortran support will make TensorFlow more accessible to a wider range of users, including scientific and engineering applications.
So how does TensorFlow support Fortran? The platform uses the Eigen library for linear algebra operations, which has been ported to Fortran. This means that users can write their TensorFlow code in Fortran and compile it using the Eigen library. In addition, TensorFlow has also added support for the ComputeCpp SYCL framework, which will enable users to target a range of devices, including GPUs and FPGAs.
The addition of Fortran support to TensorFlow is a significant development that will make the platform more accessible to a wider range of users.
What are the Future Plans for TensorFlow and Fortran Support?
TensorFlow is an open source deep learning platform that has recently added support for Fortran. This means that developers can now use TensorFlow to create and train deep learning models using this powerful programming language.
So far, TensorFlow’s Fortran support has been very well received by the development community. In fact, many developers are already using TensorFlow to create and train deep learning models for a variety of purposes.
It is clear that TensorFlow’s support for Fortran is here to stay. So what does this mean for the future of TensorFlow and Fortran support?
There are no plans to remove TensorFlow’s support for Fortran any time soon. In fact, the team behind TensorFlow is committed to continue improving and expanding its Fortran support.
This is good news for developers who want to use TensorFlow to create and train deep learning models. With TensorFlow’s continued support for Fortran, developers can expect to see even more advances in this area in the future.
In May, Google released a developer preview of TensorFlow with Fortran support. At the time, Google said that the Fortran support was “experimental” and noted that “the Fortran 2003 standard is required to use this feature.” Today, Google announced that the experimental tag has been removed and TensorFlow now officially supports Fortran.
TensorFlow, the popular open source machine learning platform, now supports the Fortran programming language. This means that developers can now use TensorFlow to write programs inFortran, a programming language commonly used in scientific and engineering applications.
The support for Fortran is the result of a collaboration between Google and IBM, two companies that are both major contributors to the TensorFlow project. The collaboration was announced at the annual Supercomputing conference, which is being held this week in Dallas, Texas.
“TensorFlow is now the world’s most popular machine learning platform and supports a growing ecosystem of libraries and tools,” said Jeff Dean, Google Senior Fellow and lead of Google Brain. “We’re excited to collaborate with IBM to bring TensorFlow’s powerful capabilities to the Fortran community.”
“As AI workloads continue to increase in complexity, traditional processing architectures are struggling to keep pace,” said Dario Gil, Vice President of AI and IBM Research. “By teaming up with Google to bring TensorFlow’s advanced capabilities to Fortran programmers, we’re opening up new opportunities for scientific and commercial users who can now leverage AI to solve some of their most challenging problems.”
About the Author
TensorFlow is Google Brain’s open source machine learning platform. It is used by researchers and developers to create sophisticated, tuneable models that are both fast and portable. TensorFlow makes it easy for beginners and experts to create machine learning models for desktop, mobile, web, and cloud.
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