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SIMD: Introduce tracer for enabled CPU targets on each optimized function (numpy#24420)
* SIMD: Cleanup the cpu dispatcher by moving disutils helper macros into a seprated header This should should be removed once we drop the support of disutils * SIMD: Introduce tracer for enabled CPU targets on each optimized function This update introduces a tracer mechanism that enables tracking of the enabled targets for each optimized function in the NumPy library. With this enhancement, it becomes possible to precisely monitor the enabled CPU dispatch targets for the dispatched functions. A new function named `opt_func_info` has been added to the new namespace `numpy.lib.introspect` module, offering this tracing capability. This function allows you to retrieve information about the enabled targets based on function names and data type signatures. Here's an example of how to use it: ```python >> func_info = numpy.lib.introspect.opt_func_info(func_name='add|abs', signature='float64|complex64') >> print(json.dumps(func_info, indent=2)) { "absolute": { "dd": { "current": "SSE41", "available": "SSE41 baseline(SSE SSE2 SSE3)" }, "Ff": { "current": "FMA3__AVX2", "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)" }, "Dd": { "current": "FMA3__AVX2", "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)" } }, "add": { "ddd": { "current": "FMA3__AVX2", "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)" }, "FFF": { "current": "FMA3__AVX2", "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)" } } } ``` For tracer utilization, remember to invoke the new `NPY_CPU_DISPATCH_TRACE()` macro either before or after employing `NPY_CPU_DISPATCH_CALL()` for dispatching. For more clarification, please refer to the header `numpy/core/src/common/npy_cpu_dispatch.h`. As part of this solution, a new dictionary, `__cpu_targets_info__`, has been introduced within the `numpy.core._multiarray_umath` module. This dictionary contains relevant data about enabled targets for each optimized function. As of now, the tracing mechanism covers ufunc-based functions, `argmax`, and `argmin` However, functions like sorting operations may require refactoring due to the tracer's associated cost. It's noteworthy that the tracer should be called only once during the initialization of Python C functions to avoid performance regressions. * DOC: Add a release note for CPU Optimization Tracking
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‎doc/release/upcoming_changes/24420.new_feature.rst

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Improved CPU Optimization Tracking
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----------------------------------
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Introduces a tracer mechanism that enables tracking of the enabled targets
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for each optimized function in the NumPy library. With this enhancement,
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it becomes possible to precisely monitor the enabled CPU dispatch
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targets for the dispatched functions.
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A new function named `opt_func_info` has been added to the new namespace `numpy.lib.introspect`,
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offering this tracing capability. This function allows you to retrieve information
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about the enabled targets based on function names and data type signatures.
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‎doc/source/reference/simd/build-options.rst

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@@ -385,3 +385,42 @@ this will disable ``AVX2`` and ``FMA3``::
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NPY_DISABLE_CPU_FEATURES="AVX2,FMA3"
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If the feature is not available, a warning will be emitted.
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Tracking dispatched functions
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-----------------------------
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Discovering which CPU targets are enabled for different optimized functions is achievable
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through the Python function ``numpy.lib.introspect.opt_func_info``.
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This function offers the flexibility of applying filters using two optional arguments:
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one for refining function names and the other for specifying data types in the signatures.
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For example::
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>> func_info = numpy.lib.introspect.opt_func_info(func_name='add|abs', signature='float64|complex64')
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>> print(json.dumps(func_info, indent=2))
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{
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"absolute": {
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"dd": {
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"current": "SSE41",
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"available": "SSE41 baseline(SSE SSE2 SSE3)"
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},
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"Ff": {
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"current": "FMA3__AVX2",
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"available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
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},
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"Dd": {
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"current": "FMA3__AVX2",
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"available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
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}
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},
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"add": {
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"ddd": {
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"current": "FMA3__AVX2",
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"available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
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},
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"FFF": {
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"current": "FMA3__AVX2",
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"available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
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}
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}
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}
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‎meson_cpu/main_config.h.in

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#define @P@_CPU_CAT__(a, b) a ## b
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#define @P@_CPU_CAT_(a, b) @P@_CPU_CAT__(a, b)
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#define @P@_CPU_CAT(a, b) @P@_CPU_CAT_(a, b)
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#define @P@_CPU_STRINGIFY(x) #x
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#define @P@_CPU_TOSTRING(x) @P@_CPU_STRINGIFY(x)
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/**
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* @def @P@WITH_CPU_BASELINE_CALL(EXEC_CB, ...)
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*/
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#define @P@WITH_CPU_DISPATCH_CALL(EXEC_CB, ...) \
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@WITH_CPU_DISPATCH_CALL@
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/*
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* Defines the default behavior for the configurable macros derived from the configuration header
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* that is generated by the meson function `mod_features.multi_targets()`.
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* #elif defined(@P@HAVE_SSE3)
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* // CODE
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* #else
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* // Fallback code in case of features enabled
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* // Fallback code in case of no features enabled
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* #endif
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* }
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* @endif
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* @param NAME The base name of the dispatched function or variable.
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*/
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#ifdef @P@MTARGETS_CURRENT
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// '@P@MTARGETS_CURRENT': only defined by the dispatchable sources
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// '@P@MTARGETS_CURRENT': only defined by the dispatch targets
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// within the meson function `mod_features.multi_targets()`
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#define @P@CPU_DISPATCH_CURFX(NAME) @P@_CPU_CAT(@P@_CPU_CAT(NAME, _), @P@MTARGETS_CURRENT)
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#else
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#define @P@CPU_DISPATCH_CURFX(NAME) @P@_CPU_EXPAND(NAME)
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#endif
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/**
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* @def @P@CPU_DISPATCH_DECLARE(...)
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*
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@P@MTARGETS_CONF_DISPATCH(@P@CPU_HAVE, @P@CPU_DISPATCH_CALL_XB_CB_, __VA_ARGS__) \
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((void) 0 /* discarded expression value */)
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/**
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* @def @P@CPU_DISPATCH_INFO(...)
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*
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* Returns an array of two strings containing the enabled target names
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* in each multi-target source.
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*
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* The first item represents the currently dispatched target,
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* while the second item contains the available targets that
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* can potentially be dispatched based on CPU capabilities.
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*
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* @code
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* #include "arithmetic.dispatch.h" // generated config file
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* const char *enabled_targets[] = @P@CPU_DISPATCH_INFO();
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*
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* printf("Current dispatched target: %s\n", enabled_targets[0]);
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* printf("Available targets: %s\n", enabled_targets[1]);
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* @endcode
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*/
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#define @P@CPU_DISPATCH_INFO() \
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{ \
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@P@MTARGETS_CONF_DISPATCH(@P@CPU_HAVE, @P@CPU_DISPATCH_INFO_HIGH_CB_, DUMMY) \
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@P@MTARGETS_CONF_BASELINE(@P@CPU_DISPATCH_INFO_BASE_HIGH_CB_, DUMMY) \
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"", \
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@P@MTARGETS_CONF_DISPATCH(@P@CPU_HAVE, @P@CPU_DISPATCH_INFO_CB_, DUMMY) \
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@P@MTARGETS_CONF_BASELINE(@P@CPU_DISPATCH_INFO_BASE_CB_, DUMMY) \
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""\
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}
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#define @P@CPU_DISPATCH_INFO_HIGH_CB_(TESTED_FEATURES, TARGET_NAME, ...) \
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(TESTED_FEATURES) ? @P@_CPU_TOSTRING(TARGET_NAME) :
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#define @P@CPU_DISPATCH_INFO_BASE_HIGH_CB_(...) \
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(1) ? "baseline(" @P@WITH_CPU_BASELINE ")" :
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// Preprocessor callbacks
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#define @P@CPU_DISPATCH_INFO_CB_(TESTED_FEATURES, TARGET_NAME, ...) \
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@P@_CPU_TOSTRING(TARGET_NAME) " "
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#define @P@CPU_DISPATCH_INFO_BASE_CB_(...) \
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"baseline(" @P@WITH_CPU_BASELINE ")"
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/**
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* Macro @P@CPU_DISPATCH_CALL_ALL(...)
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*

‎numpy/core/code_generators/generate_umath.py

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if cfunc_fname:
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funclist.append(cfunc_fname)
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if t.dispatch:
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dispdict.setdefault(t.dispatch, []).append((name, k, cfunc_fname))
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dispdict.setdefault(t.dispatch, []).append(
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(name, k, cfunc_fname, t.in_ + t.out)
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)
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else:
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funclist.append('NULL')
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#include "{dname}.dispatch.h"
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#endif
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"""))
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for (ufunc_name, func_idx, cfunc_name) in funcs:
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for (ufunc_name, func_idx, cfunc_name, inout) in funcs:
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code2list.append(textwrap.dedent(f"""\
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NPY_CPU_DISPATCH_TRACE("{ufunc_name}", "{''.join(inout)}");
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NPY_CPU_DISPATCH_CALL_XB({ufunc_name}_functions[{func_idx}] = {cfunc_name});
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"""))
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return "\n".join(code1list), "\n".join(code2list)

‎numpy/core/meson.build

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'src/common/ufunc_override.c',
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'src/common/numpyos.c',
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'src/common/npy_cpu_features.c',
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'src/common/npy_cpu_dispatch.c',
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src_file.process('src/common/templ_common.h.src')
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]
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if have_blas

‎numpy/core/setup.py

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join('src', 'common', 'ufunc_override.c'),
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join('src', 'common', 'numpyos.c'),
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join('src', 'common', 'npy_cpu_features.c'),
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join('src', 'common', 'npy_cpu_dispatch.c'),
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]
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if os.environ.get('NPY_USE_BLAS_ILP64', "0") != "0":

‎numpy/core/src/common/npy_cpu_dispatch.c

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#include "npy_cpu_dispatch.h"
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static PyObject *npy__cpu_dispatch_registery = NULL;
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NPY_VISIBILITY_HIDDEN int
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npy_cpu_dispatch_tracer_init(PyObject *mod)
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{
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if (npy__cpu_dispatch_registery != NULL) {
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PyErr_Format(PyExc_RuntimeError, "CPU dispatcher tracer already initlized");
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return -1;
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}
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PyObject *mod_dict = PyModule_GetDict(mod);
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if (mod_dict == NULL) {
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return -1;
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}
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PyObject *reg_dict = PyDict_New();
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if (reg_dict == NULL) {
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return -1;
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}
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int err = PyDict_SetItemString(mod_dict, "__cpu_targets_info__", reg_dict);
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Py_DECREF(reg_dict);
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if (err != 0) {
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return -1;
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}
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npy__cpu_dispatch_registery = reg_dict;
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return 0;
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}
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NPY_VISIBILITY_HIDDEN void
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npy_cpu_dispatch_trace(const char *fname, const char *signature,
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const char **dispatch_info)
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{
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PyObject *func_dict = PyDict_GetItemString(npy__cpu_dispatch_registery, fname);
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if (func_dict == NULL) {
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func_dict = PyDict_New();
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if (func_dict == NULL) {
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return;
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}
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int err = PyDict_SetItemString(npy__cpu_dispatch_registery, fname, func_dict);
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Py_DECREF(func_dict);
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if (err != 0) {
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return;
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}
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}
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// target info for each signature
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PyObject *sig_dict = PyDict_New();
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if (sig_dict == NULL) {
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return;
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}
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int err = PyDict_SetItemString(func_dict, signature, sig_dict);
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Py_DECREF(sig_dict);
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if (err != 0) {
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return;
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}
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// current dispatched target
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PyObject *current_target = PyUnicode_FromString(dispatch_info[0]);
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if (current_target == NULL) {
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return;
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}
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err = PyDict_SetItemString(sig_dict, "current", current_target);
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Py_DECREF(current_target);
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if (err != 0) {
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return;
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}
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// available targets
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PyObject *available = PyUnicode_FromString(dispatch_info[1]);
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if (available == NULL) {
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return;
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}
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err = PyDict_SetItemString(sig_dict, "available", available);
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Py_DECREF(available);
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if (err != 0) {
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return;
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}
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}

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