2a7ca101d7
Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream: Added: - python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc. Includes 204 .py files with full test coverage for all 27 algorithms - ci/ (163 files) — Build/test infrastructure build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml Directly maps to our [INFRA-CI] and [INFRA-BUILD] items - .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md - docs/ (491 files) — Official CCCL documentation CI references, CMake guides, Python compute docs, libcudacxx PTX docs - test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar) - Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml - CLAUDE.md symlink → AGENTS.md (NVIDIA's standard) cccl_upstream now mirrors full NVIDIA/cccl structure: Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks) After: 53M (+python +ci +docs +.agent +test +configs) This completes the CCCL base needed for: - [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds - [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations - [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh - Agent workflow: .agent/skills/ for consistent style and test patterns
96 lines
3.7 KiB
ReStructuredText
96 lines
3.7 KiB
ReStructuredText
.. _cccl-development-module-debugger-setup:
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=================
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General Debugging
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=================
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Debugger Pretty Printers
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========================
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libcudacxx ships custom pretty printers for its types under
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``libcudacxx/share/libcudacxx``. They render CCCL types in a readable form and, for
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device-accessible data, copy the contents back to the host so the elements can be
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inspected. Two independent implementations are provided:
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- ``libcudacxx/share/libcudacxx/gdb`` - printers for GDB.
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- ``libcudacxx/share/libcudacxx/lldb`` - printers for LLDB.
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Each directory has an ``__init__.py`` entry point that registers every printer. The
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repository root contains a ``.gdbinit`` and a ``.lldbinit`` that load the matching entry
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point for you, so the simplest way to enable the printers is to let the debugger pick up
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these files.
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.. important::
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``lldb`` and ``gdb`` only inspect the following locations when looking for init
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dotfiles (in the given order):
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#. Home directory config files (usually ``~/.lldbinit`` or ``~/.config/gdb/gdbinit`` on
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Linux, but check the respective manuals for specifics).
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#. The current working directory.
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They do **not** walk up the directory stack like most tools. So if you have a
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``.lldbinit`` in the parent directory, ``lldb`` will **not** load it. For this reason,
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you **must** run the debugger from the root CCCL directory in order for automatic
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loading of the pretty printers to work.
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In addition to not loading parent directory dot-files, ``gdb`` or ``lldb`` will load not
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dotfiles unless you explicitly allow them. The following sections explain how to enable
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this for each debugger.
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.. note::
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The following is **not** needed when working inside a devcontainer. devcontainers
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already have the following set up.
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If they don't, and automatic loading of the pretty printers does not work, then this is
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a bug and should be fixed.
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It is only needed for bare metal builds.
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GDB
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---
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By default GDB does not source a ``.gdbinit`` from the current directory, and it guards
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auto-loaded scripts with the ``auto-load safe-path`` setting. Add the repository root to
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your ``~/.gdbinit`` (or ``~/.config/gdb/gdbinit`` if you have ``XDG_CONFIG_HOME`` set) so
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the project's ``.gdbinit`` is trusted and loaded::
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add-auto-load-safe-path /absolute/path/to/cccl
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set auto-load local-gdbinit on
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Launch GDB from the repository root and the printers should register automatically.
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Verify that the printers are active with ``info pretty-printer``.
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To load the printers without depending on the working directory - for example
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from a global ``~/.gdbinit`` - ``source`` the entry point by absolute path
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instead::
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source /absolute/path/to/cccl/libcudacxx/share/libcudacxx/gdb/__init__.py
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``source`` runs the script directly and is not subject to the ``auto-load safe-path``
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restriction.
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LLDB
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----
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LLDB only reads ``.lldbinit`` from your home directory unless you opt in to loading one
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from the current working directory. Enable that once in your ``~/.lldbinit`` (``lldb``
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seemingly does not respect ``XDG_CONFIG_HOME``)::
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settings set target.load-cwd-lldbinit true
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This is a trust decision, since the local file runs arbitrary Python. Launch LLDB from the
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repository root and the project's ``.lldbinit`` imports the formatters automatically.
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To load the formatters without depending on the working directory, add the absolute path
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to your ``~/.lldbinit`` instead::
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command script import "/absolute/path/to/cccl/libcudacxx/share/libcudacxx/lldb/__init__.py"
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The entry point's ``__lldb_init_module`` hook defines and enables an LLDB type category
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for the formatters. Print any CCCL value with the usual commands (``v``, ``frame
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variable``, or ``dwim-print``).
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