Jiqun Tu – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2023-06-12T09:05:04Z http://www.open-lab.net/blog/feed/ Jiqun Tu <![CDATA[Constructing CUDA Graphs with Dynamic Parameters]]> http://www.open-lab.net/blog/?p=52463 2023-06-12T09:05:04Z 2022-08-23T18:33:32Z Ever since its introduction in CUDA 10, CUDA Graphs has been used in a variety of applications. A graph groups a set of CUDA kernels and other CUDA operations...]]>

Ever since its introduction in CUDA 10, CUDA Graphs has been used in a variety of applications. A graph groups a set of CUDA kernels and other CUDA operations together and executes them with a specified dependency tree. It speeds up the workflow by combining the driver activities associated with CUDA kernel launches and CUDA API calls. It also enforces the dependencies with hardware accelerations…

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Jiqun Tu <![CDATA[Running Python UDFs in Native NVIDIA CUDA Kernels with the RAPIDS cuDF]]> http://www.open-lab.net/blog/?p=18849 2022-08-21T23:40:21Z 2020-07-09T23:01:06Z In this post, I introduce a design and implementation of a framework within RAPIDS cuDF that enables compiling Python user-defined functions (UDF) and inlining...]]>

In this post, I introduce a design and implementation of a framework within RAPIDS cuDF that enables compiling Python user-defined functions (UDF) and inlining them into native CUDA kernels. This framework uses the Numba Python compiler and Jitify CUDA just-in-time (JIT) compilation library to provide cuDF users the flexibility of Python with the performance of CUDA as a compiled language.

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