dtourolle/KPN
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Performance improvements, better readme and complete python bindings
🧪 Test / test (push) Failing after 28m30s
Details

Browse Source
This commit is contained in:
dtourolle
2026-05-12 21:23:33 +02:00
parent c39db82763
commit f6bcaa15b0
38 changed files with 4679 additions and 846 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md.in
+402
View File
@@ -0,0 +1,402 @@
# KPN++
A C++20 Kahn Process Network (KPN) library. Each node wraps a function and runs in its own thread, communicating with downstream nodes via bounded FIFO channels. Includes Python bindings via nanobind.
---
## Requirements
| Dependency | Version | Notes |
|---|---|---|
| CMake | ≥ 3.21 | |
| C++ compiler | GCC ≥ 11, Clang ≥ 13, MSVC 19.29 | C++20 required |
| Threads | system | `find_package(Threads)` |
| nanobind | ≥ 2.1 | auto-fetched if not installed; Python ≥ 3.8 |
| Catch2 | v3 | auto-fetched for tests |
| Google Test | v1.14 | auto-fetched for tests |
| OpenCV | ≥ 4 | optional; only for example 09 |
---
## Build
```bash
cmake -B build -DKPN_BUILD_PYTHON=OFF # core + tests + C++ examples
cmake --build build --parallel
ctest --test-dir build
```
Enable Python bindings (requires nanobind and Python dev headers):
```bash
cmake -B build -DKPN_BUILD_PYTHON=ON
cmake --build build --parallel
```
Disable examples:
```bash
cmake -B build -DKPN_BUILD_EXAMPLES=OFF
```
---
## Core Concepts
### Nodes
A node wraps any callable. Its input types are taken from the function's parameter list; its output types from the return type. Multi-output nodes return `std::tuple<...>`.
```cpp
#include <kpn/kpn.hpp>
using namespace kpn;
```
Source, transform, and sink — from [`examples/01_hello_pipeline/main.cpp`](examples/01_hello_pipeline/main.cpp):
<!-- @snippet examples/01_hello_pipeline/main.cpp basic_node_fns -->
Multi-output node returning a tuple — from [`examples/03_multi_output/main.cpp`](examples/03_multi_output/main.cpp):
<!-- @snippet examples/03_multi_output/main.cpp multi_output_fn -->
### Creating Nodes
**Index-only ports** (from [`examples/01_hello_pipeline/main.cpp`](examples/01_hello_pipeline/main.cpp)):
<!-- @snippet examples/01_hello_pipeline/main.cpp index_only_nodes -->
**Named ports** (from [`examples/02_named_ports/main.cpp`](examples/02_named_ports/main.cpp)):
<!-- @snippet examples/02_named_ports/main.cpp named_port_creation -->
**Multi-named output source** (from [`examples/09_opencv_cellshade/main.cpp`](examples/09_opencv_cellshade/main.cpp)):
```cpp
auto src = make_node<capture>(out<"colour","grey">{}, 8);
```
Port names are NTTP `fixed_string` values — resolved entirely at compile time, zero runtime cost.
### Building a Network
`Network` is **non-owning** — declare nodes first, then register them. Nodes must outlive the network.
From [`examples/02_named_ports/main.cpp`](examples/02_named_ports/main.cpp):
<!-- @snippet examples/02_named_ports/main.cpp named_port_network -->
`.build()` runs cycle detection — throws `NetworkCycleError` on cycles.
> **Named port syntax in template context:** when the node variable is `auto`-deduced, use `.template output<"name">()` and `.template input<"name">()` to help the parser.
### Channel Semantics
- **Bounded FIFO**: default capacity 5, configurable per-node at construction.
- **Blocking `pop()`**: consumer blocks until data is available (KPN semantics).
- **Throwing `push()`**: throws `ChannelOverflowError` if the channel is full and accepting.
- **Silent drop on disabled channel**: after `node.stop()`, its input channels are disabled — producers that push into them have the value silently dropped. No exception, no blocking.
- **Source throttling**: source nodes (no inputs) must sleep or yield to avoid overflowing downstream FIFOs. See example 09.
### Storage Policy
Large types (`sizeof > 8` or non-trivially-copyable) are stored as `std::shared_ptr<const T>` inside the channel — no copies, shared immutable ownership. Small trivially-copyable types are stored by value.
Override the policy for a specific type (from [`examples/04_storage_policy/main.cpp`](examples/04_storage_policy/main.cpp)):
<!-- @snippet examples/04_storage_policy/main.cpp storage_policy_spec -->
### Diagnostics & Error Handling
Custom diagnostics handler — fires on the watchdog interval (from [`examples/05_error_handling/main.cpp`](examples/05_error_handling/main.cpp)):
<!-- @snippet examples/05_error_handling/main.cpp diagnostics_handler -->
### Shutdown
`node.stop()` / `net.stop()`:
1. Sets `accepting_ = false` on all input channels (drops in-flight pushes silently).
2. Clears any queued items from those channels.
3. Unblocks any thread blocked on `pop()` (throws `ChannelClosedError` inside `run_loop`, which exits cleanly).
4. Joins the node thread.
---
## Named Ports — Design Notes
Port names use C++20 NTTP `fixed_string`. The deduction guide is required:
```cpp
template<std::size_t N>
fixed_string(const char (&)[N]) -> fixed_string<N>;
```
`fixed_string<4>` and `fixed_string<7>` are distinct types — `input<"img">()` and `input<"sigma">()` resolve to different template instantiations at compile time. Wrong names produce a `static_assert` at the call site with a readable message.
---
## Sub-Networks
`Network` implements `INode`, so it can be nested inside a larger `Network`:
```cpp
// Inner sub-network
Network pipe;
pipe.add("pre", pre_node)
.add("enh", enh_node)
.connect("pre", pre_node.output<0>(), "enh", enh_node.input<0>())
.expose_input("img", pre_node.input<0>())
.expose_output("result", enh_node.output<0>())
.build();
// Outer network
Network top;
top.add("pipe", pipe)
.add("sink", sink_node)
.connect("pipe", pipe.output<"result">(), "sink", sink_node.input<0>())
.build();
top.start();
```
---
## Display / GUI Nodes
**Do not wrap `imshow`/`waitKey` as a KPN node.** Qt and Wayland require these to run on the main thread (the thread that owns the event loop). Instead, derive from `MainThreadNode<>` — it owns the input channels, implements `INode`, and exposes a `step()` method to call on the main thread.
`DisplayNode` from [`examples/09_opencv_cellshade/main.cpp`](examples/09_opencv_cellshade/main.cpp):
<!-- @snippet examples/09_opencv_cellshade/main.cpp display_node -->
Wire it into the network and drive it from the main thread:
<!-- @snippet examples/09_opencv_cellshade/main.cpp main_thread_step -->
---
## OpenCV Cell-Shading Example
Real-time cell-shading pipeline from [`examples/09_opencv_cellshade/main.cpp`](examples/09_opencv_cellshade/main.cpp).
**Source node** — returns two frames (colour + grey) as a tuple, routing them to separate downstream branches:
<!-- @snippet examples/09_opencv_cellshade/main.cpp capture_fn -->
**Full network wiring:**
<!-- @snippet examples/09_opencv_cellshade/main.cpp opencv_network -->
---
## Fan-Out (Multi-Output)
From [`examples/03_multi_output/main.cpp`](examples/03_multi_output/main.cpp) — one node fans out to two independent sinks via a tuple return:
<!-- @snippet examples/03_multi_output/main.cpp fanout_network -->
---
## Python Bindings
> Python bindings are scaffolded but not yet fully implemented. See `python/kpn_python.cpp` and `include/kpn/python/bindings.hpp`.
A `PyNetwork` is constructed from a closed list of C++ node types. The variant of all port types is derived at compile time — no runtime type registration needed.
**GIL rules (non-negotiable):**
- Acquire the GIL only for the duration of a Python callable invocation.
- Release the GIL before any blocking channel operation (`pop()`, `push()`, `net.read()`, `net.write()`).
Violating the second rule deadlocks.
---
## Examples
| Example | What it shows |
|---|---|
| `01_hello_pipeline` | Linear pipeline, index-based port wiring |
| `02_named_ports` | `in<>`/`out<>` name tags, named port access |
| `03_multi_output` | Tuple-returning node, per-element sub-port routing |
| `04_storage_policy` | `channel_storage_policy` default and specialisation |
| `05_error_handling` | `ChannelOverflowError`, `ErrorHandler` |
| `06_watchdog` | Watchdog interval, stall detection |
| `07_python_network` | PyNetwork, pure Python node *(pending)* |
| `08_python_subport` | `net.read`, `net.write`, sub-port tap *(pending)* |
| `09_opencv_cellshade` | Real-time cell-shading on webcam/pattern; requires OpenCV ≥ 4 |
Run the cell-shading example:
```bash
./build/examples/09_opencv_cellshade
# Press 'q' or close the window to stop.
# Falls back to an animated synthetic pattern if no webcam is found.
```
---
## Performance
Measured on Linux (x86-64, `-O3 -march=native`) with `benchmarks/bench_pipeline`.
Each topology pushes N items through the graph; `overhead_us/item` strips out the
per-node compute time to isolate framework cost.
Overhead formula: `(elapsed − (N + depth − 1) × work_us) / N` removes the expected
pipeline-fill cost so the number reflects pure framework latency.
### Baseline overhead (private pools, 100 µs/node)
| Topology | items/sec | overhead µs/item |
|---|---|---|
| chain depth-1 | 9 797 | ~2 |
| chain depth-4 | 9 448 | ~4 |
| chain depth-8 | 9 078 | ~7 |
| chain depth-16 | 7 004 | ~13 ← oversubscription |
| chain depth-32 | 4 179 | ~77 ← oversubscription |
| wide fanout-1 | 9 751 | ~3 |
| wide fanout-4 | 9 668 | ~3 |
| diamond (2×2) | 9 607 | ~4 |
Chain overhead is flat at **~2–7 µs/hop** for depths within the machine's core count,
then rises once threads compete for CPU. Wide and diamond topologies add no measurable
overhead as fanout increases — all branches run in parallel.
### Scheduling modes
`Node<>` gives each node a private `ThreadPool(1)`. `PoolNode<>` lets multiple
nodes share one pool. The right choice depends on the graph shape:
| Scenario | Recommended |
|---|---|
| Work per node < 100 µs, deep chain | Private pools — lower per-hop latency |
| Work per node ≥ 100 µs, wide/diamond | Shared pool, `threads = hardware_concurrency` |
| Any graph, bounded thread count required | Shared pool, `threads ≥ max parallel nodes` |
A shared single-thread pool (`threads=1`) fully serialises the graph — throughput
divides by depth for chains and by width for fanout topologies. A shared pool with
`threads ≥ max_concurrent_nodes` matches private-pool throughput while keeping the
OS thread count bounded.
### vs. TBB flow graph
Benchmarked against `tbb::flow::function_node<int,int>` (serial concurrency) with
`tbb::flow::broadcast_node<int>` for fanout. Run with `cmake -DKPN_BUILD_BENCHMARKS=ON`
— TBB benchmarks are included automatically when `find_package(TBB)` succeeds.
**Channel implementation:** lock-free SPSC ring buffer with `std::atomic::wait/notify_one`
(C++20 portable futex) plus a configurable spin-before-sleep window (default ~4 µs).
Large types are stored as `shared_ptr<const T>` — fanout copies reference counts,
not data.
Overhead µs/item at **work_us = 10** (framework overhead dominates):
| Topology | KPN private | TBB |
|---|---|---|
| chain depth-1 | 1.7 | **1.4** |
| chain depth-4 | 2.5 | **2.2** |
| chain depth-8 | **3.0** | 3.6 |
| chain depth-16 | **9.3** | 13.0 |
| chain depth-32 | 23.2 | **14.2** |
| wide fanout-4 | 2.5 | **1.4** |
| diamond (2×2) | 3.4 | **1.9** |
Overhead µs/item at **work_us = 100** (moderate compute, KPN wins):
| Topology | KPN private | TBB |
|---|---|---|
| chain depth-1 | **2.1** | 3.5 |
| chain depth-4 | **4.3** | 5.2 |
| chain depth-8 | **6.7** | 8.5 |
| chain depth-16 | **12.8** | 17.4 |
| chain depth-32 | **77** | 81 |
| wide fanout-4 | 3.4 | **1.9** |
| diamond (2×2) | **4.1** | 6.1 |
KPN private pools beat TBB for every chain and diamond topology at 100 µs/node, and
match TBB within ~20% at 10 µs/node for shallow chains. TBB retains an edge on wide
fanout (serial dispatch loop vs. work-stealing pool) and at extreme oversubscription
depths (chain-32 at 10 µs). The remaining gap at light work is the cost of
`atomic::wait` vs. TBB's continuously-spinning worker threads.
### vs. TBB — API
The function signature is the node. KPN infers input and output types automatically;
there is no graph object to manage.
**Single-output node:**
```cpp
// KPN — 1 line
int scale(int x) { return x * 2; }
// TBB — must state types, concurrency policy, and carry a graph reference
tbb::flow::function_node<int,int> n(g, tbb::flow::serial, [](int x){ return x*2; });
```
**Multi-output node:**
```cpp
// KPN — return a tuple
std::tuple<cv::Mat,cv::Mat> split(cv::Mat f) { return {f, f}; }
// TBB — multifunction_node + explicit try_put per port
tbb::flow::multifunction_node<cv::Mat, std::tuple<cv::Mat,cv::Mat>> n(
g, tbb::flow::serial,
[](cv::Mat f, auto& ports) {
std::get<0>(ports).try_put(f);
std::get<1>(ports).try_put(f);
});
```
**Named ports** — compile-time checked, zero runtime cost, not available in TBB:
```cpp
auto node = make_node<split>(in<"frame">{}, out<"colour","grey">{}, 5);
net.connect("cam", cam.output<"frame">(), "split", node.input<"frame">());
// ^^^^^^^ typo → compile error
```
| | KPN | TBB |
|---|---|---|
| Node definition | plain function | `function_node<In,Out>` + explicit types |
| Multi-output | `return std::tuple<A,B>` | `multifunction_node` + `try_put` × N |
| Named ports | `in<"name">` / `out<"name">` compile-time | none |
| Graph lifetime | none | `graph g` must outlive all nodes |
| Shutdown | `net.stop()` | `g.wait_for_all()` + manual |
| Python bindings | designed-in | none |
Build the benchmarks with:
```bash
cmake -B build -DKPN_BUILD_BENCHMARKS=ON
cmake --build build --target bench_pipeline
./build/benchmarks/bench_pipeline | tee results.csv
```
---
## Project Structure
```
include/kpn/
fixed_string.hpp — NTTP string, in<>/out<> tags, index_of
traits.hpp — function_traits, normalised_return_t, output_count_v
channel.hpp — Channel<T>, channel_storage_policy, exceptions
port.hpp — InputPort<N,I>, OutputPort<N,I>
node.hpp — Node<Func,in<...>,out<...>>, make_node, INode
network.hpp — Network (builder, cycle detection, watchdog)
variant_node.hpp — VariantNode, PythonConverter<T>, unique_types (Python layer)
python/
bindings.hpp — nanobind helpers, GIL rule documentation
kpn.hpp — umbrella header
src/
network.cpp — non-template Network implementation
tests/
test_fixed_string.cpp
test_traits.cpp
test_channel.cpp
test_node.cpp
test_network.cpp
python/
kpn_python.cpp — nanobind module entry point
examples/
01_hello_pipeline/ … 09_opencv_cellshade/
scripts/
render_readme.py — regenerates README.md from README.md.in
```