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48 lines
2.2 KiB
ReStructuredText
48 lines
2.2 KiB
ReStructuredText
.. _libc_gpu_motivation:
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==========================
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Motivation and Limitations
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==========================
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Motivation
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==========
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This project aims to provide a large subset of the C standard library to users
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of GPU accelerators. We deliberately choose to only implement a subset of the C
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library as some features are not expressly useful or easily implemented on the
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GPU. This will be discussed further in `Limitations <libc_gpu_limitations>`_.
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The main motivation behind this project is to provide the well understood C
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library as a firm base for GPU development.
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The main idea behind this project is that programming GPUs can be as
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straightforward as programming on CPUs. This project aims to validate the GPU as
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a more general-purpose target. The implementations here will also enable more
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complex implementations of other libraries on the GPU, such as ``libc++``.
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Host services and C library features are currently provided sparsely by the
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different GPU vendors. We wish to provide these functions more completely and
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make their implementations available in a common format. This is useful for
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targets like OpenMP offloading or SYCL which wish to unify the offloading
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toolchain. We also aim to provide these functions in a format compatible with
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offloading in ``Clang`` so that we can treat the C library for the GPU as a
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standard static library.
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A valuable use for providing C library features on the GPU is for testing. For
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this reason we build `tests on the GPU <libc_gpu_testing>`_ that can run a unit
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test as if it were being run on the CPU. This also helps users port applications
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that traditionally were run on the CPU. With this support, we can expand test
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coverage for the GPU backend to the existing LLVM C library tests.
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.. _libc_gpu_limitations:
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Limitations
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===========
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We only implement a subset of the standard C library. The GPU does not
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currently support thread local variables in all cases, so variables like
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``errno`` are atomic and global. Furthermore, the GPU under the OpenCL execution
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model cannot safely provide a mutex interface. This means that features like
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file buffering are not implemented on the GPU. We can also not easily provide
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threading features on the GPU due to the execution model so these will be
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ignored, as will features like ``locale`` or ``time``.
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