Performance on Spacemit K3, thanks @edolnx for testing
master:
Total time (ms) : 65200
Nodes searched : 3493826
Nodes/second : 53586
riscv-scalable-port:
Total time (ms) : 15834
Nodes searched : 3493826
Nodes/second : 220653
Also thanks to @camel-cdr for guidance on RVV programming, and https://cloud-v.co for supplying an RVV instance to test with
passed STC:
LLR: 2.81 (-2.94,2.94) <0.00,2.00>
Total: 1152 W: 527 L: 108 D: 517
Ptnml(0-2): 0, 17, 167, 348, 44
https://tests.stockfishchess.org/tests/view/6a39895b3036e45021aeb368
## Summary
We've had a `riscv64` target for a while, but haven't really optimized for it, in particular the vector extension (RVV).
RVV, like SVE, is based on a scalable vector system where the vector length ranges from 128 to 65536. In practice implementations are between 128 and 2048, and 256 bits is quite common (e.g. the Spacemit K3 system above). Unfortunately this doesn't fit well into the rest of our code which assumes a fixed vector length, so what I've done is bypass the `VECTOR` ifdef (which now basically means "FIXED_LENGTH_VECTOR") and just have RVV-specific paths.
The ability to explicitly control `vl` makes the code quite readable, in my opinion. We use LMUL>1 in most places to take advantage of multi-vector instructions. Generally the LMULs were chosen to best support a 256-bit vlen, which is very common, but by virtue of how the vlen control works, the code works with any vlen. In a couple places, i.e., `get_changed_pieces` and `AffineTransformSparseInput::propagate`, we have separate implementations depending on the vlen, because the optimal LMUL varies a lot between implementations.
One little wrinkle is that `load_as` is compiled to a sequence of byte loads, because although unaligned loads are legal in RVA23, the spec says that they *may* be extremely slow (even though they usually aren't, in actual hw), so compilers are conservative. Thus I aligned the relevant buffers and made the semantics of `load_as` that the operand is aligned, by adding a runtime assertion.
### Universal binary
Adding a universal binary is pretty easy and we can just cross-compile. There are two targets: baseline rv64gc and riscv64-rva23, which is actually a smaller subset of RVA23 that also works on some older processors that don't support the full thing. We use clang because GCC, until recently, has a nasty bug with LTO and RVV.
Like the universal ARM and x86 builds, we check all the builds in CI. In this case we run bench with multiple vlens, 128 through 1024.
In the meantime I deleted the existing broken and unused riscv64 tests.
### Follow-ups
- Optimizations
- zvdot4a8i path
closes https://github.com/official-stockfish/Stockfish/pull/6920
No functional change
- Add new target `macos-lipo`.
- Created by compiling a universal x86 binary (no PGO) and a standard Apple silicon binary (with PGO), then combining them into a Mach-O fat binary
- To keep only one copy of the net, we add custom loading logic in the x86 section. The executable reads its own path and mmaps the net that's in the ARM section.
- The offset and size (from the executable base) of the mapping is injected after compilation in `patch_x86_slice.sh`
- avx512 on macOS isn't advertised in the xcr0 register by default. The simple solution I came up with is to execute a dummy AVX512 instruction, which sets up the register, before calling `__builtin_cpu_init`.
Some housekeeping as well:
- Rename `armv8-universal` -> `arm64-universal`.
- Add standard copyright headers to the files we've added recently.
Potential follow-ups:
- Disservin's Makefile cleanup
- Alternative ideas for the net loading. In particular, this will error out if the user strips the binary (since that'll invalidate the offset).
closes https://github.com/official-stockfish/Stockfish/pull/6860
No functional change
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* .tar -> .tar.gz: save a few more MB in distribution.
* drop android armv7 without NEON support: there should be almost no devices around that do not support this.
closes https://github.com/official-stockfish/Stockfish/pull/6850
No functional change
- We add a new path for supporting universal builds without #embed . `xxd` causes the compiler to run out of memory, so instead we embed it as a string literal created at compile time.
- This file is created in `net.sh`, and only if `--embed-dir` isn't supported + we are doing a universal build.
- This was necessary because Android NDK seems to not support embed, idk why
- A couple other Makefile tweaks were necessary for the Android path.
- While we're at it, remove the non-universal arm64 windows and android binaries.
closes https://github.com/official-stockfish/Stockfish/pull/6827
No functional change
Introduce the armv8-universal target. 🥴
The entry point is essentially the same as x86's, except we no longer have access to `__builtin_cpu_supports` so instead we need an OS-specific query for whether we support dotprod. The Makefile is modified to support both universal builds.
If in the future we add more ARM targets, such as SVE, we'll need to add qemu to the RUN_PREFIX in CI, because currently we assume (for PGO purposes) that the CI host supports all the used ARM instructions.
### clang/Windows
The painful part here is clang on Windows, which, until arm64 mingw is stabilized, is required for targeting arm64. This PR also gets it to work for x86. In the Makefile this setup corresponds to `use_lto_emit_asm=yes`.
In particular, `--defsym` and `--save-temps` are not supported by `lld-link`, and objcopy `--rename-section` doesn't work on COFF binaries because of how section names work there.
- `--defsym` is needed to define `main` for PGO purposes and assigns it to the namespaced, per-arch main function. Instead, we define `main` in `main.cpp` so that the compilation is successful, then delete it before the final link.
- Instead of `--save-temps` to get the LTO intermediate object, we pass `--lto-emit-asm` to the linker, which outputs `stockfish.exe.lto.s`.
- Finally, we have a small AWK script to find the `.ctors` section, neuter it, and put start/stop symbols around it with the same naming scheme as ELF (`__start_*_init`/`__stop_*_init`).
I'm lowk a Windows programming noob so if there's simpler ways of going about this, I'd appreciate a pointer. @PikaCat-OuO + Codex used an approach that involved going in and modifying the LLVM bitcode, but that felt more complicated to me.
closes https://github.com/official-stockfish/Stockfish/pull/6823
No functional change
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Rename Linux universal release package from
`stockfish-ubuntu-x86-64-universal.tar.gz` to
`stockfish-linux-x86-64-universal.tar.gz` (and similar for the binary), as the
bundled binary should run on any Linux distro with glibc >= 2.35 (which is the
glibc version of the Ubuntu 22.04 build server).
Note that the Linux universal binary is built with static libstdc++ linkage, so
this adds no extra dependency.
This change will hopefully make it less confusing for users, and in line with
how we show it on stockfishchess.org (as Linux).
closes https://github.com/official-stockfish/Stockfish/pull/6760
No functional change
`stockfish-ubuntu-x86-64-universal.tar` goes from 94.8MiB to 67.4MiB (tar.gz)
Note that the CI code is written such that it easy to select other compression
schemes in the future (e.g. tar.xz) by simply changing the `archive_ext`
parameter.
closes https://github.com/official-stockfish/Stockfish/pull/6746
No functional change
When vnni256 was first introduced #3038 it was very slightly faster than vnni512
on some machines. We have since sped up vnni512 significantly (#4796 over 10%
alone, #6139, and probably others I'm forgetting). Since any machine that can
run vnni256 can run vnni512 this arch is no longer useful.
Note, x86-64-avxvnni still covers targets that don't have AVX512 but do have
VNNI on 128- and 256-bit vectors.
closes https://github.com/official-stockfish/Stockfish/pull/6340
No functional change
Allow for NUMA memory replication for NNUE weights. Bind threads to ensure execution on a specific NUMA node.
This patch introduces NUMA memory replication, currently only utilized for the NNUE weights. Along with it comes all machinery required to identify NUMA nodes and bind threads to specific processors/nodes. It also comes with small changes to Thread and ThreadPool to allow easier execution of custom functions on the designated thread. Old thread binding (WinProcGroup) machinery is removed because it's incompatible with this patch. Small changes to unrelated parts of the code were made to ensure correctness, like some classes being made unmovable, raw pointers replaced with unique_ptr. etc.
Windows 7 and Windows 10 is partially supported. Windows 11 is fully supported. Linux is fully supported, with explicit exclusion of Android. No additional dependencies.
-----------------
A new UCI option `NumaPolicy` is introduced. It can take the following values:
```
system - gathers NUMA node information from the system (lscpu or windows api), for each threads binds it to a single NUMA node
none - assumes there is 1 NUMA node, never binds threads
auto - this is the default value, depends on the number of set threads and NUMA nodes, will only enable binding on multinode systems and when the number of threads reaches a threshold (dependent on node size and count)
[[custom]] -
// ':'-separated numa nodes
// ','-separated cpu indices
// supports "first-last" range syntax for cpu indices,
for example '0-15,32-47:16-31,48-63'
```
Setting `NumaPolicy` forces recreation of the threads in the ThreadPool, which in turn forces the recreation of the TT.
The threads are distributed among NUMA nodes in a round-robin fashion based on fill percentage (i.e. it will strive to fill all NUMA nodes evenly). Threads are bound to NUMA nodes, not specific processors, because that's our only requirement and the OS can schedule them better.
Special care is made that maximum memory usage on systems that do not require memory replication stays as previously, that is, unnecessary copies are avoided.
On linux the process' processor affinity is respected. This means that if you for example use taskset to restrict Stockfish to a single NUMA node then the `system` and `auto` settings will only see a single NUMA node (more precisely, the processors included in the current affinity mask) and act accordingly.
-----------------
We can't ensure that a memory allocation takes place on a given NUMA node without using libnuma on linux, or using appropriate custom allocators on windows (https://learn.microsoft.com/en-us/windows/win32/memory/allocating-memory-from-a-numa-node), so to avoid complications the current implementation relies on first-touch policy. Due to this we also rely on the memory allocator to give us a new chunk of untouched memory from the system. This appears to work reliably on linux, but results may vary.
MacOS is not supported, because AFAIK it's not affected, and implementation would be problematic anyway.
Windows is supported since Windows 7 (https://learn.microsoft.com/en-us/windows/win32/api/processtopologyapi/nf-processtopologyapi-setthreadgroupaffinity). Until Windows 11/Server 2022 NUMA nodes are split such that they cannot span processor groups. This is because before Windows 11/Server 2022 it's not possible to set thread affinity spanning processor groups. The splitting is done manually in some cases (required after Windows 10 Build 20348). Since Windows 11/Server 2022 we can set affinites spanning processor group so this splitting is not done, so the behaviour is pretty much like on linux.
Linux is supported, **without** libnuma requirement. `lscpu` is expected.
-----------------
Passed 60+1 @ 256t 16000MB hash: https://tests.stockfishchess.org/tests/view/6654e443a86388d5e27db0d8
```
LLR: 2.95 (-2.94,2.94) <0.00,10.00>
Total: 278 W: 110 L: 29 D: 139
Ptnml(0-2): 0, 1, 56, 82, 0
```
Passed SMP STC: https://tests.stockfishchess.org/tests/view/6654fc74a86388d5e27db1cd
```
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 67152 W: 17354 L: 17177 D: 32621
Ptnml(0-2): 64, 7428, 18408, 7619, 57
```
Passed STC: https://tests.stockfishchess.org/tests/view/6654fb27a86388d5e27db15c
```
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 131648 W: 34155 L: 34045 D: 63448
Ptnml(0-2): 426, 13878, 37096, 14008, 416
```
fixes#5253
closes https://github.com/official-stockfish/Stockfish/pull/5285
No functional change
This refactors the CI workflows to group some
logic and makes sure that all (pre)release
binaries are actually tested.
The screenshot below shows the execution logic of
the reworked ci,
https://github.com/Disservin/Stockfish/actions/runs/7773581379.
You can also hover over the cards to see the
execution flow.
The `matrix.json` and `arm_matrix.json` define the
binaries which will be uploaded to GitHub.
Afterwards a matrix is created and each job
compiles a profile guided build for that arch and
uploads that as an artifact to GitHub. The
Binaries/ARM_Binaries workflow's are called when
the previous step has been completed, and uploads
all artifacts to the (pre)release.
This also fixes some indentations and renames the
workflows, see
https://github.com/official-stockfish/Stockfish/actions,
where every workflow is called `Stockfish` vs
https://github.com/Disservin/Stockfish/actions. It
also increases the parallel compilation used for
make from `-j2 to -j4`.
It now also prevents the prerelease action from
running on forks.
A test release can be viewed here
https://github.com/Disservin/Stockfish/releases.
closes https://github.com/official-stockfish/Stockfish/pull/5035
No functional change
