NVIDIA has three notable GPU platforms, namely GeForce, Quadro, and Tesla, that support general- purpose computation. At the higher end of the GeForce series are the consumer-level GPUs that GPU computing enthusiasts are usually interested in for running GPU-accelerated applications at a lower budget range (with the exception of the Titan series). On the higher budget perspective, the Quadro and Tesla lineup are specifically targeted toward GPU-accelerated computational applications. A lot of features for such applications are available only on Quadro and Tesla GPUs. All GPUs belonging to these three platforms differ in performance and features. They have transitioned to different micro-architectures through the years since their inception.
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You're reading from Hands-On GPU Computing with Python
Avimanyu Bandyopadhyay is currently pursuing a PhD degree in Bioinformatics based on applied GPU computing in Computational Biology at Heritage Institute of Technology, Kolkata, India. Since 2014, he developed a keen interest in GPU computing, and used CUDA for his master's thesis. He has experience as a systems administrator as well, particularly on the Linux platform. Avimanyu is also a scientific writer, technology communicator, and a passionate gamer. He has published technical writing on open source computing and has actively participated in NVIDIA's GPU computing conferences since 2016. A big-time Linux fan, he strongly believes in the significance of Linux and an open source approach in scientific research. Deep learning with GPUs is his new passion!
Read more about Avimanyu Bandyopadhyay
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Avimanyu Bandyopadhyay is currently pursuing a PhD degree in Bioinformatics based on applied GPU computing in Computational Biology at Heritage Institute of Technology, Kolkata, India. Since 2014, he developed a keen interest in GPU computing, and used CUDA for his master's thesis. He has experience as a systems administrator as well, particularly on the Linux platform. Avimanyu is also a scientific writer, technology communicator, and a passionate gamer. He has published technical writing on open source computing and has actively participated in NVIDIA's GPU computing conferences since 2016. A big-time Linux fan, he strongly believes in the significance of Linux and an open source approach in scientific research. Deep learning with GPUs is his new passion!
Read more about Avimanyu Bandyopadhyay