Add build time optimization documentation

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Max Podkorytov
2026-01-19 13:17:42 -06:00
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# Build Time Optimization
This document describes techniques for reducing C++ template instantiation overhead in the Composable Kernel codebase.
## Why Build Time Matters
Composable Kernel relies heavily on C++ template metaprogramming to achieve GPU kernels with no runtime abstraction penalty. However, deep template instantiation can significantly impact build times. A single translation unit may trigger hundreds of thousands of template instantiations, with each instantiation adding to compile time.
## Measuring Build Time
Use Clang's `-ftime-trace` flag to generate JSON build traces:
```bash
# Build with time trace enabled
cmake -DCMAKE_CXX_FLAGS="-ftime-trace -ftime-trace-granularity=1" ..
ninja example_gemm_xdl_fp16
# Find the trace file
find . -name "*.json" -path "*/CMakeFiles/*"
```
The trace file can be viewed in Chrome's `chrome://tracing` or analyzed with tools like [ClangBuildAnalyzer](https://github.com/aras-p/ClangBuildAnalyzer).
Key metrics to monitor:
- **Template instantiation count**: Total number of unique template instantiations
- **Template instantiation depth**: Maximum recursion depth during instantiation
- **Wall-clock time**: Actual time spent instantiating templates
The `script/tools/ck-build-analysis` script automates trace collection and analysis:
```bash
script/tools/ck-build-analysis example_gemm_xdl_fp16 --granularity=1
```
## Optimization Techniques
### 1. Replace O(N) Recursion with O(1) Pack Expansion
Recursive template patterns create O(N) instantiation depth. Use compiler intrinsics and fold expressions for O(1) depth.
**Before** (O(N) recursive instantiation):
```cpp
template <index_t N, typename F, index_t... Is>
struct sequence_gen_impl
{
using type = typename sequence_gen_impl<N-1, F, F{}(Number<N-1>{}), Is...>::type;
};
template <typename F, index_t... Is>
struct sequence_gen_impl<0, F, Is...>
{
using type = Sequence<Is...>;
};
```
**After** (O(1) using compiler intrinsic):
```cpp
template <index_t N, typename F>
struct sequence_gen
{
template <index_t... Is>
static constexpr auto make(std::integer_sequence<index_t, Is...>)
{
return Sequence<F{}(Number<Is>{})...>{};
}
using type = decltype(make(__make_integer_seq<std::integer_sequence, index_t, N>{}));
};
```
The `__make_integer_seq` intrinsic (available in Clang and MSVC) generates integer sequences with O(1) template depth.
### 2. Replace Lambdas with Named Functors
Each lambda expression creates a unique closure type, causing separate template instantiations at every call site.
**Before** (lambda creates unique instantiations):
```cpp
// Called in multiple places - each creates new instantiations
auto result = transform_tensor_descriptor(
desc,
make_tuple(make_pass_through_transform(Length)),
make_tuple(Sequence<0>{}),
make_tuple(Sequence<0>{}));
// The lambda inside transform_tensor_descriptor:
generate_tuple([](auto i) { return Sequence<i>{}; }, Number<N>{});
```
**After** (named functor shares instantiations):
```cpp
// Define functor once
struct generate_identity_sequence
{
template <index_t I>
__host__ __device__ constexpr auto operator()(Number<I>) const
{
return Sequence<I>{};
}
};
// Use everywhere - shares instantiations
generate_tuple(generate_identity_sequence{}, Number<N>{});
```
This reduced `transform_tensor_descriptor` instantiations from 388 to 32 (92% reduction).
#### container_concat optimization
The same pattern applies to utility functions like `container_concat`:
**Before**:
```cpp
template <typename... X, typename... Y>
__host__ __device__ constexpr auto container_concat(const Tuple<X...>& tx, const Tuple<Y...>& ty)
{
return unpack2([](auto&&... zs) { return make_tuple(forward<decltype(zs)>(zs)...); }, tx, ty);
}
```
**After**:
```cpp
struct make_tuple_functor
{
template <typename... Ts>
__host__ __device__ constexpr auto operator()(Ts&&... xs) const
{
return make_tuple(forward<Ts>(xs)...);
}
};
template <typename... X, typename... Y>
__host__ __device__ constexpr auto container_concat(const Tuple<X...>& tx, const Tuple<Y...>& ty)
{
return unpack2(make_tuple_functor{}, tx, ty);
}
```
This reduced `container_concat` instantiations from 186 to 93 (50% reduction).
#### make_uniform_tuple helper
For patterns that create tuples with repeated values, use dedicated helpers instead of lambdas:
**Before**:
```cpp
// Creates unique lambda type at each call site
generate_tuple([](auto) { return some_value; }, Number<N>{});
```
**After**:
```cpp
// Defined once, shared across all call sites
template <index_t N, typename T>
__host__ __device__ constexpr auto make_uniform_tuple(T&& value)
{
return detail::make_uniform_tuple_impl(static_cast<T&&>(value), make_index_sequence<N>{});
}
// Usage
make_uniform_tuple<N>(some_value);
```
### 3. Use Constexpr Arrays Instead of Template Recursion
Replace recursive template searches with constexpr functions using arrays.
**Before** (O(N) recursive template search):
```cpp
template <index_t Target, typename FirstSeq, typename... RestSeqs>
struct find_in_tuple_of_sequences_impl
{
static constexpr index_t pos = sequence_find<Target>(FirstSeq{});
static constexpr bool found_here = (pos >= 0);
using next = find_in_tuple_of_sequences_impl<Target, RestSeqs...>;
static constexpr index_t itran = found_here ? 0 : 1 + next::itran;
static constexpr index_t idim_up = found_here ? pos : next::idim_up;
};
```
**After** (O(1) pack expansion with constexpr array):
```cpp
template <index_t Target, typename... Seqs>
struct FindInTupleOfSequencesCompute
{
static constexpr auto compute()
{
if constexpr(sizeof...(Seqs) == 0) {
return ResultData{0, 0, false};
} else {
// Pack expansion creates array - O(1) template depth
constexpr index_t indices[] = {sequence_find_value<Target>(Seqs{})...};
for(index_t i = 0; i < sizeof...(Seqs); ++i)
if(indices[i] >= 0) return ResultData{i, indices[i], true};
return ResultData{0, 0, false};
}
}
};
```
This reduced instantiations by 50% and wall-clock time by 69%.
### 4. Avoid Unnecessary Template Parameter Variations
Templates with many parameter combinations cause combinatorial explosion.
- Cache template results where possible
- Use type erasure for runtime-only variations
- Consider `if constexpr` to reduce branch template instantiations
## Case Studies
The following PRs demonstrate these techniques applied to Composable Kernel:
- **sequence_gen optimization**: Replaced O(N) recursion with `__make_integer_seq` intrinsic
- **transform_tensor_descriptor**: Replaced lambdas with named functors (92% instantiation reduction)
- **container_concat**: Replaced lambdas with named functors (50% instantiation reduction)
- **find_in_tuple_of_sequences**: Replaced recursive search with pack expansion (50% reduction)
- **sequence_merge**: Replaced O(log N) recursion with O(1) fold expression
See tracking issue [#3575](https://github.com/ROCm/composable_kernel/issues/3575) for the full list of PRs.
## Tools and Commands
Identify optimization targets:
```bash
# Run analysis on a specific target
script/tools/ck-build-analysis example_convnd_fwd_xdl_fp16 --granularity=1
# View the generated report
cat build_time_analysis_report.md
```
The report shows template instantiation counts, wall-clock times, and identifies the most expensive templates.