[GPU] New device-level ops for QIPC#693
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Aligns the subgroup scope with `block.sync()` and the planned
`block.mem_fence()` / `grid.mem_fence()` naming. The old names remain
as thin aliases that forward to the new ones and emit a
DeprecationWarning on first use (per-alias one-shot guard, plus the
existing `warnings.filterwarnings("once", DeprecationWarning, ...)`
in `quadrants.lang.misc`).
Updates `docs/source/user_guide/subgroup.md` to describe the renames
as done (with deprecation aliases) rather than planned.
Brings the four previously partial / TODO data-movement ops up to full
CUDA + AMDGPU + SPIR-V coverage:
* shuffle_up: add CUDA + AMDGPU lowerings.
- CUDA: new `cuda_shuffle_up_{i32,f32,i64,f64}` runtime helpers in
runtime_module/runtime.cpp (mirroring `cuda_shuffle_down_*`), built
on the already-patched `cuda_shfl_up_sync_{i32,f32}` NVVM intrinsics.
Codegen branch + `emit_cuda_shuffle_up` in codegen/cuda/codegen_cuda.cpp.
- AMDGPU: new `amdgpu_shuffle_up_{i32,f32,i64,f64}` runtime helpers
using the existing `ds_bpermute` path (same FIXME re: DPP fast-path
as `shuffle_down`). Codegen branch + `emit_amdgpu_shuffle_up`.
* shuffle_xor and broadcast_first: replace TODO `pass` stubs with
portable `@qd.func` wrappers that inline into the calling kernel:
- `shuffle_xor(value, mask)` ≡ `shuffle(value, u32(lane) ^ mask)`
- `broadcast_first(value)` ≡ `broadcast(value, u32(0))`
No backend codegen / runtime changes required: every backend that
lowers `shuffle` / `broadcast` now lowers these too.
Tests:
* test_subgroup_shuffle_up (mirror of test_subgroup_shuffle_down)
* test_subgroup_shuffle_xor (uses the new wrapper directly; the
existing `_pattern` test continues to verify the manual emulation)
* test_subgroup_broadcast_first
Doc: refresh `docs/source/user_guide/subgroup.md` data-movement
support matrix + per-op semantics + performance notes to reflect
universal coverage. Drop the now-stale "fail to link on CUDA / AMDGPU"
paragraph from the `shuffle_up` section.
Adds the missing test coverage for the rename half of this PR: * test_subgroup_sync (vulkan): smoke that subgroup.sync() — the renamed subgroup.barrier() — traces and runs. * test_subgroup_mem_fence (vulkan): same for subgroup.mem_fence(). * test_subgroup_barrier_deprecation_warn_once: pure-Python unit test asserting subgroup.barrier() emits exactly one DeprecationWarning across multiple calls and forwards to sync(); monkeypatches sync to a no-op so no kernel context is required and the test runs on every arch. * test_subgroup_memory_barrier_deprecation_warn_once: mirror for subgroup.memory_barrier() / subgroup.mem_fence().
… + SPIR-V The data-movement ops in qd.simt.subgroup require uniform control flow with all lanes active (already documented in subgroup.md). Under that contract subgroups (warps / waves) execute in lockstep on CUDA and AMDGPU, so an intra-subgroup control barrier or memory fence is a no-op on those backends. The SPIR-V backend keeps the real OpControlBarrier / OpMemoryBarrier emission because Vulkan / Metal subgroups can diverge. Lower subgroupBarrier / subgroupMemoryBarrier to a placeholder i32 0 (matching the SPIR-V codegen's return convention) on the CUDA and AMDGPU codegen, so calling subgroup.sync() / subgroup.mem_fence() from a kernel succeeds on every GPU backend. The smoke tests for sync()/mem_fence() are now arch=qd.gpu rather than arch=qd.vulkan and confirm tracing + running on each backend. Doc: matrix updated to yes/yes/yes (with a footnote explaining the no-op-on-CUDA/AMDGPU semantics) and the per-op section rewritten to describe the universal lowering.
…+ AMDGPU + SPIR-V" This reverts commit 233b08c. The "no-op on CUDA / AMDGPU" lowering conflated control-flow lockstep with memory ordering. The two are not equivalent: * `sync()` (control barrier) under our uniform-CF + all-lanes-active contract really is a no-op on CUDA / AMDGPU, because warps / waves are already at the same program point. That part was defensible. * `mem_fence()` (memory fence) is NOT a no-op. Lockstep execution does not order memory operations: the compiler may reorder loads / stores across the call, and the SM may buffer writes. A correct CUDA lowering would need at minimum an LLVM `fence` intrinsic with the appropriate scope (or `__threadfence_block()` as an over-strict fallback). That was not done. Rather than ship a half-correct lowering, restore the previous status: both ops remain SPIR-V only, the doc keeps its original "warps are lockstep, these are typically unnecessary; use __syncwarp under divergent control flow" guidance, and the smoke tests stay on arch=qd.vulkan. Implementing real CUDA / AMDGPU lowerings can be a separate, properly-thought-through change.
…GPU + SPIR-V
Replaces the earlier (reverted) attempt that lowered these to no-ops on CUDA / AMDGPU
"because warps are lockstep", which was wrong about what the user contract guarantees:
sync() must reconverge lanes that have been split by independent thread scheduling
(Volta+) and mem_fence() must actually order memory. This change wires real backend
primitives into the lowering and fixes a long-standing SPIR-V mem_fence() bug.
Per-backend lowerings
---------------------
sync() (subgroupBarrier):
* SPIR-V : already correct - OpControlBarrier(Subgroup, Subgroup, 0).
* CUDA : warp_barrier(0xFFFFFFFF), reusing the existing runtime helper that is
patched to llvm.nvvm.bar.warp.sync (i.e. __syncwarp). This is the
precise warp-scope reconvergence primitive Volta+ needs and is a no-op
under uniform CF on Pascal.
* AMDGPU : llvm.amdgcn.wave.barrier - LLVM's wave-scope sync primitive. Acts as a
compiler reordering barrier on GCN (lockstep) and emits a real wave
barrier on RDNA where waves can span multiple SIMDs.
mem_fence() (subgroupMemoryBarrier):
* SPIR-V : was emitting OpMemoryBarrier(Subgroup, 0). The Memory Semantics operand
must have an ordering bit AND at least one storage class, so 0 is
invalid; drivers that accept it treat the instruction as a no-op. Now
emits AcquireRelease | UniformMemory | WorkgroupMemory, matching what
workgroupMemoryBarrier does (just at Subgroup scope).
* CUDA : block_memfence(), patched to llvm.nvvm.membar.cta (__threadfence_block).
Workgroup-scope, hence over-strict for the subgroup-scope ask but
correct - a CTA-scope fence orders memory across the whole CTA, of
which the subgroup is a strict subset.
* AMDGPU : LLVM 'fence syncscope("workgroup") seq_cst' - lowers to the appropriate
s_waitcnt / cache-flush sequence. Same workgroup-scope over-strictness
note.
Tests
-----
test_subgroup_sync and test_subgroup_mem_fence flip from arch=qd.vulkan to
arch=qd.gpu and now run on every GPU backend. They are smoke tests: they verify
the kernel traces, codegens, and runs without error. We do not attempt to
construct a producer/consumer race that only the fence makes legal - that kind of
test is hard to write portably and easy to make flaky.
Doc updates
-----------
The Identification-and-control table now shows yes for sync() / mem_fence() across
all backends, with a footnote on mem_fence() pointing out the workgroup-scope
over-strictness on CUDA / AMDGPU. The semantics section spells out the per-backend
lowering and the uniform-CF caller contract.
…s CUDA + AMDGPU + SPIR-V
Closes the last two `no` cells in the Identification-and-control matrix in subgroup.md.
Both ops now lower correctly on every GPU backend.
group_size()
------------
* CUDA: returns the static constant 32 (warp size on every supported NVIDIA arch).
* AMDGPU: emits llvm.amdgcn.wavefrontsize; the AMDGPU backend folds it to 32 or 64
based on the function's +wavefrontsize32/+wavefrontsize64 target feature.
* SPIR-V: unchanged - was already querying OpSubgroupSize.
elect()
-------
Reimplemented as a @qd.func wrapper:
@func
def elect():
return i32(invocation_id() == 0)
Inlines at trace time into compare + zext on every backend. Replaces the SPIR-V-only
OpGroupNonUniformElect path with a portable definition.
Semantic change worth flagging
------------------------------
OpGroupNonUniformElect is allowed to elect any *active* lane and may pick a different
lane on different invocations. The new wrapper deterministically elects lane 0.
Under qd.simt.subgroup's documented uniform-CF + all-lanes-active contract this is
strictly compatible (lane 0 is always active and is a legal SPIR-V choice), and it
makes the behaviour identical across backends. Grepped the codebase before changing -
no internal caller depends on the broader OpGroupNonUniformElect semantics.
Tests
-----
* test_subgroup_group_size: every lane writes group_size() into a buffer; the result
must be uniform across lanes and in {32, 64}.
* test_subgroup_elect: writes elect(), invocation_id(), and group_size() into per-lane
slots, then asserts (a) elect() is in {0, 1}, (b) elected lanes are exactly the
invocation_id == 0 lanes, and (c) the elected count equals N / group_size.
Both parametrized over arch=qd.gpu so they run on every available GPU backend.
Doc
---
subgroup.md matrix flips both rows to yes-on-all. Semantics sections describe each
backend lowering and call out the elect() lane-0-pinning narrowing of SPIR-V.
… + AMDGPU + SPIR-V Replaces the SPIR-V-only `subgroup.inclusive_add(v)` with a portable sized variant implemented as a `@qd.func` Hillis-Steele scan over `shuffle_up`. This is the first slice of the planned migration of the inclusive_* / exclusive_* ops to a universal sized API; the other 6 inclusive_* ops still take `(value)` and lower via OpGroupNonUniformInclusiveScan on SPIR-V only. Implementation -------------- @func def inclusive_add(value, log2_size: template()): lane_in_group = invocation_id() & ((1 << log2_size) - 1) for i in static(range(log2_size)): offset = static(1 << i) partner = shuffle_up(value, u32(offset)) if lane_in_group >= offset: value = value + partner return value * `shuffle_up` is in uniform CF (every lane participates) - matches its documented contract on every backend. * The `if lane_in_group >= offset` is per-lane arithmetic - no subgroup op inside the conditional. * Cross-group `shuffle_up` partners are masked off by the lane_in_group guard, so groups smaller than the full subgroup compose correctly when log2_size < log2(group_size). Backend cleanup --------------- * Dropped `subgroupInclusiveAdd` from the SPIR-V codegen `inclusive_scan_ops` set in `quadrants/codegen/spirv/spirv_codegen.cpp` - that path is now unreachable for `inclusive_add`. The other 6 inclusive ops still go through that branch. * Dropped `PER_INTERNAL_OP(subgroupInclusiveAdd)` from internal_ops.inc.h and `POLY_OP(subgroupInclusiveAdd, ...)` from type_system.cpp. No SPIR-V fast path left to keep alive. Internal caller fix ------------------- `quadrants.algorithms.PrefixSumExecutor` was passing `subgroup.inclusive_add` as a template-callable to `scan_add_inclusive`, which invokes it as `inclusive_add(val)` with one argument. After the API change this would TypeError. Added a single-arg adapter `subgroup_inclusive_add_warp_i32` next to `warp_shfl_up_i32` in `_kernels.py` that calls `subgroup.inclusive_add(val, 5)` (log2_size=5 -> 32-lane warp/wave scan, matching WARP_SZ in the kernel), and routed the Vulkan branch to the adapter. The CUDA branch still uses `warp_shfl_up_i32` for now. Tests ----- `test_subgroup_inclusive_add` (arch=qd.gpu, parametrized over `log2_size in 1..5` and `dtype in {i32, i64, u64, f32, f64}`): runs the scan and verifies each lane's result against a Python running sum. Doc --- * Matrix flips `inclusive_add` row to yes-on-all (with the same `*` AMDGPU perf-asterisk as `reduce_add`). * Top-of-section text and "Performance notes" updated to reflect that `inclusive_add` now has a portable sized form, while the other inclusive_* ops are still mid-migration. * The "Inclusive scan on SPIR-V" example now uses `inclusive_add(v, 5)` and works on every GPU backend.
… AMDGPU + SPIR-V Slice 2 of the inclusive_* / exclusive_* migration: extends the same portable @qd.func Hillis-Steele pattern from `inclusive_add` (slice 1) to the other six inclusive ops, sharing a single `_inclusive_scan` helper. Implementation -------------- @func def _inclusive_scan(value, op: template(), log2_size: template()): lane_in_group = invocation_id() & ((1 << log2_size) - 1) for i in static(range(log2_size)): offset = static(1 << i) partner = shuffle_up(value, u32(offset)) if lane_in_group >= offset: value = op(value, partner) return value @func def inclusive_add(v, log2_size): return _inclusive_scan(v, _bin_add, log2_size) @func def inclusive_mul(v, log2_size): return _inclusive_scan(v, _bin_mul, log2_size) ... (min / max / and / or / xor follow the same one-line pattern) The seven `_bin_*` are tiny @func wrappers around `+`, `*`, `min(a,b)`, `max(a,b)`, `a & b`, `a | b`, `a ^ b`. Each is passed as a template-callable to `_inclusive_scan` and gets inlined at trace time, so the public API has the same cost as the slice 1 inline scan: log2_size shuffle+op pairs, no runtime indirection. This refactors the existing `inclusive_add` (which lived inline in slice 1) onto the shared helper at the same time, so all seven scans live in one place. The externally-observable behaviour of `inclusive_add` is unchanged. Backend cleanup --------------- * Removed the entire `inclusive_scan_ops` / `OpGroupNonUniformInclusiveScan` branch from `quadrants/codegen/spirv/spirv_codegen.cpp` - all seven ops now go through the portable Python path on every backend, including SPIR-V. * Removed the six remaining `subgroupInclusive{Mul,Min,Max,And,Or,Xor}` entries from `internal_ops.inc.h` and `type_system.cpp`. Tests ----- * Added `test_subgroup_inclusive_{mul,min,max,and,or,xor}` (arch=qd.gpu), each parametrized over `log2_size in 1..5` and a per-op dtype list: - `_mul`: i32, f32, f64 (inputs clamped to [1, 4] so 32-way product fits i32). - `_min` / `_max`: i32, f32, f64 (varied non-monotonic inputs). - `_and` / `_or` / `_xor`: i32, i64, u64 (bit-varied inputs). * Refactored the existing `test_subgroup_inclusive_add` to share a small `_check_inclusive_scan` helper with the new tests; the dtype matrix is unchanged (i32, i64, u64, f32, f64). Doc --- * Matrix flips all six remaining `inclusive_*` rows to yes-on-all (with `*` for AMDGPU - same ds_bpermute perf note as `inclusive_add`). * Section header collapses the seven ops into a single block: same shape, only the operator differs. * Performance notes call out that `OpGroupNonUniformInclusiveScan` is no longer used on SPIR-V even though it was supported - the trade-off is uniform cost across backends. The `exclusive_*` ops are still TODO stubs - that's slice 3.
…s i32 The previous `(i % 4) + 1` pattern produced cycles of 1*2*3*4 = 24 per group of 4; over 28 lanes that's 24^7 ≈ 4.6e9, which overflows i32 (and was the only failure in the cuda-side slice 2 run). Replace with `2 if i % 4 == 0 else 1`: max 8 twos in 32 lanes → product ≤ 2**8 == 256, well within i32 and exact in f32.
Slice 3 (final) of the inclusive_* / exclusive_* migration: replaces the seven TODO-stub `exclusive_*` functions with portable @qd.func implementations layered on top of the inclusive scans from slice 2. Implementation -------------- @func def _exclusive_scan(value, op: template(), identity, log2_size: template()): inc = _inclusive_scan(value, op, log2_size) shifted = shuffle_up(inc, u32(1)) lane_in_group = invocation_id() & ((1 << log2_size) - 1) result = shifted if lane_in_group == 0: result = identity return result The lane-0 substitution is required: `shuffle_up` with offset 1 is implementation-defined at lane 0 (and `OpGroupNonUniformShuffleUp` calls it undefined outright), so we cannot rely on whatever the hardware happens to produce there. Identity per op is supplied as a runtime expression in `value`'s dtype, derived from `value` itself so the wrapper does not need to inspect the dtype: add: value - value (zero) mul: value - value + 1 (one - the literal +1 takes value's dtype) or: value ^ value (zero) xor: value ^ value (zero) and: ~(value ^ value) (all bits set) For `min` and `max` there is no portable type-extreme that can be derived from `value` alone, so those two ops take an explicit `identity` argument: exclusive_min(v, log2_size, identity) # pass +inf or dtype max exclusive_max(v, log2_size, identity) # pass -inf or dtype min Cost per call: one inclusive scan (`log2_size` shuffle+op pairs) plus one extra `shuffle_up` and a per-lane select. Tests ----- * Added `test_subgroup_exclusive_{add,mul,min,max,and,or,xor}` (arch=qd.gpu), each parametrized over `log2_size in 1..5` and a per-op dtype list: - `_add`: i32, i64, u64, f32, f64 - `_mul`: i32, f32, f64 (inputs bounded so 32-way product fits i32) - `_min` / `_max`: i32, f32, f64 (caller passes explicit identity) - `_and` / `_or` / `_xor`: i32, i64, u64 * Shared `_check_exclusive_scan` helper drives the kernel launch, dtype skip, and per-lane verification: lane 0 must equal the supplied identity, lane k>0 must equal the op-reduce of `src[0..k]`. Doc --- * Matrix gains all seven `exclusive_*` rows, all yes-on-all (with `*` for AMDGPU same as inclusive_*). * New section describes the shared shuffle_up + select pattern, the per-op identity expressions, and why min/max take explicit identities. * The old "exclusive_*, all_true, any_true, all_equal" TODO-stub section is trimmed down to just the three remaining stubs.
… scans
Both `_check_inclusive_scan` and `_check_exclusive_scan` previously verified only
the first group's worth of lanes (lanes 0..group_size-1). Two coverage gaps:
1. For log2_size < 5, multiple independent groups of 2**log2_size lanes share
a single 32-lane subgroup. The `lane_in_group >= offset` mask is what
isolates them from each other - and that mask was completely untested.
A bug there would have silently passed.
2. The 64-lane launch produces two independent 32-lane subgroups (lanes 0-31
and 32-63) running the same scan side by side. Cross-subgroup leakage
in the underlying shuffle_up (e.g. an AMDGPU ds_bpermute with the wrong
mask) would not have been caught.
Both helpers now iterate over every (group, in-group-lane) pair across the full
64-lane launch and verify the expected per-lane value, recomputing the running
op-reduce from `src[group_base..]` at each group boundary.
Coverage delta: with log2_size=1 the old test verified 2 of 64 lanes; the new
test verifies all 64. At log2_size=3, 8 of 64 -> 64 of 64. At log2_size=5,
32 of 64 -> 64 of 64 (still the same group_size, but the second subgroup is
now exercised).
Validated on the cluster: all 230 scan tests (115 inclusive + 115 exclusive)
pass with the extended verification on CUDA and on Vulkan; the slice 1/2/3
implementations were already correct, this just closes the test gap.
…al fix) `exclusive_*` scans all fail on the Metal backend (via MoltenVK), with the `got` value at lane 1 of each group being whatever the inclusive scan would produce *if the lane-0 conditional update had been applied unconditionally* (eg. `inc[0] = src[0] op src[0]` instead of `inc[0] = src[0]`). For non-idempotent ops this is visibly wrong; for `and`/`or` it accidentally matches at group 0 because `x op x = x`. Inclusive scans pass because nothing downstream re-reads `inc[0]` across lanes. Root cause is reconvergence in MoltenVK's SPIR-V → MSL lowering of the pattern `if lane_in_group >= offset: value = op(value, partner)` followed by another subgroup op (the next loop iteration's `shuffle_up`, or the `shuffle_up(inc, 1)` inside `_exclusive_scan`): lanes that took the false branch end up reading stale register state from the subsequent shuffle. Fix: replace both conditional updates (`if`-then-assignment) with `qd.select`, which lowers to `OpSelect` and keeps every lane in straight-line code. `op(value, partner)` is pure so unconditional evaluation is safe. Adds a comment explaining the choice. Validated: - CUDA simt scans: 280/280 pass - Vulkan simt scans: 280/280 pass - CUDA scan+sort: 65/65 pass - Vulkan scan+sort: 65/65 pass
Replaces the long-standing TODO stubs with portable @qd.func implementations plus a CUDA fast path at full-warp size. API: - `subgroup.all_true(predicate, log2_size)` -- AND-reduce `predicate != 0` across each `2**log2_size` group, returns `i32(0|1)` broadcast to every lane. - `subgroup.any_true(predicate, log2_size)` -- OR-reduce, same shape. - `subgroup.all_equal(value, log2_size)` -- broadcast group-lane-0's value, AND-reduce per-lane equality bit. Equality is the backend's native `==` (NaN != NaN, +0.0 == -0.0), matching SPIR-V `OpGroupNonUniformAllEqual`. CUDA shortcut: at trace time, `qd.static()` on `current_cfg().arch` plus the compile-time `log2_size` selects `cuda_all_sync_i32` / `cuda_any_sync_i32` when `log2_size == 5`, so full-warp uses lower to a single `vote.all` / `vote.any` instruction with no branch in the IR. `all_equal` inherits the shortcut transitively via `all_true`. We deliberately do not wire `__match_all_sync` because it requires sm_70+ and uses bit-equality on floats, contradicting the documented `OpGroupNonUniformAllEqual` semantics. Every other backend (Vulkan, Metal, AMDGPU), and CUDA at `log2_size < 5`, falls back to a portable `shuffle_xor` butterfly: `log2_size` shuffles plus `log2_size` ANDs / ORs, fully unrolled into the calling kernel's IR (same shape as `reduce_all_add`). No C++ codegen changes. Tests cover all-true / all-false / one-odd-lane-in-one-group / sparse-pattern scenarios for `all_true` and `any_true`, and all-same / all-distinct / same-per-group / one-outlier-per-group for `all_equal`. Each scenario verifies every group across the full 64-lane launch (so the launch spans two CUDA / Metal / RDNA subgroups, exercising both partial-subgroup multi-group and cross-subgroup behaviour). Validated: - CUDA simt: 369/370 (+ 1 expected skip) - Vulkan simt: 350/370 (+20 expected MoltenVK skips) - CUDA scan+sort: 65/65 - Vulkan scan+sort: 65/65 Doc: `docs/source/user_guide/subgroup.md` updated -- support matrix, dedicated section per op, and CUDA-shortcut rationale.
The previous commit replaced `if` with `qd.select` in the scan helpers, but `OpSelect` on MoltenVK/Metal silently returns the false-branch value when an operand is an f32 produced by a shuffle intrinsic. Revert `_inclusive_scan` back to `if`, which works correctly on its own. For `_exclusive_scan`, restructure to shift the input before the inclusive scan (shuffle_up → fill lane 0 with identity → inclusive scan) instead of running the inclusive scan then shuffling the result. The old pattern triggered a separate Metal SPIR-V misoptimization where the register holding the inclusive result was clobbered when only consumed by a shuffle intrinsic. Co-authored-by: Cursor <cursoragent@cursor.com>
Two coverage gaps surfaced during a post-merge audit: * `all_true` / `any_true` were only ever exercised with predicate values 0 or 1, so the `i32(predicate != 0)` cast was untested. Adds a `nonbinary-mixed` scenario (`[((i*17) % 13) - 6 for i in range(N)]` -- mixes 0, positives, and negatives) to both tests. * `all_equal` on floats was documented as "NaN != NaN, +0.0 == -0.0" (matching `OpGroupNonUniformAllEqual`) but no test pinned the contract down. Adds `test_subgroup_all_equal_float_contract` (f32 + f64 x log2_size 1..5) covering: ±0 mixed in every group -> 1; NaN at every group start -> 0; NaN at a single lane -> only that group is 0; all NaN -> every group 0. These also lock the door against a future refactor swapping in `__match_all_sync` on CUDA (which would silently regress to bit-equality on floats). Validated: 45/45 voting tests on CUDA and Vulkan (was 35/35 + 10 new from the float contract scenarios).
* black auto-reformats in `subgroup.py` and `test_simt.py` (line-length=120 per `.pre-commit-config.yaml`). * clang-format auto-reformats in `codegen_amdgpu.cpp` and `spirv_codegen.cpp`. * Drop unused `from quadrants.lang.simt import subgroup` from `_algorithms.py` (left over after the switch to `subgroup_inclusive_add_warp_i32`); ruff re-sorts the remaining import block. * Extend the file-level pyright comment in `subgroup.py` from `reportInvalidTypeForm=false` to also disable `reportOperatorIssue` so that `p & shuffle_xor(...)` / `p | shuffle_xor(...)` in the new voting ops don't trip pyright on `Expr` operator overloads — same false-positive class the existing suppression already covers. Pre-commit (black, clang-format, ruff, pylint, trailing-whitespace, end-of-file) clean. Pyright is down to 6 pre-existing errors in files this branch does not touch (`_tensor_wrapper.py`, `_func_base.py`, `_metal_interop.py`, all from PR #618 / streams work) — net 0 new errors attributable to this branch.
The voting / scan / data-movement work landed with prose wrapped at the AI-default ~80-95c instead of the project's 120c (per `pre-commit` black config `-l 120`). Reflow the affected runs in: * `python/quadrants/lang/simt/subgroup.py` — module-level voting / inclusive / exclusive backend-strategy comments, plus `elect`, `all_true`, `any_true`, `all_equal`, `broadcast_first`, `_inclusive_scan`, all `inclusive_*` / `exclusive_*` op docstrings, and `_exclusive_scan` / `shuffle_xor`. * `tests/python/test_simt.py` — voting / scan section comments, scan verification rationale, voting predicate-truthy / float-contract notes, `test_subgroup_sync` / `_mem_fence` / `_group_size` / `_elect` / `_barrier_deprecation_warn_once` / `_memory_barrier_deprecation_warn_once` docstrings. * `python/quadrants/_kernels.py` — `subgroup_inclusive_add_warp_i32` adapter docstring. * `python/quadrants/algorithms/_algorithms.py` — comment explaining the warp-i32 adapter usage in `PrefixSumExecutor`. No semantic changes; black / pre-commit / pyright still clean. Audited via `find_underwrapped --diff origin/main`: remaining flagged runs are all at ~110-120c (only minor packing imbalance, max ≤ 123c) — no AI-default 80c under-wrapping in this branch's diff.
The CI wrap-checker flagged three C++ comment blocks in PR #665 still wrapped near ~80c (`runtime.cpp:1033`, `runtime.cpp:1136`, `codegen_amdgpu.cpp:507`). While in there I audited the rest of the new C++ subgroup commentary and the per-op intrinsic notes, and reflowed them to the project's 120c target. Also tightened a couple of Python lines that crept past 120c (one f-string docstring, one explanatory comment in test_simt.py). No semantic changes.
CI wrap-checker on PR #665 flagged three more docstring blocks wrapping at 83-87c instead of 120c (`exclusive_add`, `test_subgroup_sync`, `test_subgroup_mem_fence`). Reflow those. No semantic changes.
Stale carry-over from the days when several ops were one-backend stubs; no longer applies now that everything in the doc is universal.
Stacked on hp/cross-gpu-subgroup; same shape as the existing `reduce_add` / `reduce_all_add` pair: * `reduce_min(v, log2_size)` / `reduce_max(v, log2_size)` — `shuffle_down` tree, result valid in lane 0 of each `2**log2_size` group. * `reduce_all_min(v, log2_size)` / `reduce_all_max(v, log2_size)` — `shuffle_xor` butterfly, result broadcast to every lane. Both forms unroll into exactly `log2_size` shuffle+min (or `+max`) pairs in the calling kernel's IR — no kernel-launch overhead, no separate runtime symbol. Lowers to backend-specific min/max intrinsics (`fminnm` / `fmaxnm` on PTX, `llvm.minnum` / `llvm.maxnum` on AMDGPU, `OpFMin` / `OpFMax` on SPIR-V); float-NaN handling is documented as implementation-defined. Tests: parametrized as `qd.gpu` over `i32` / `i64` / `u64` / `f32` / `f64` and `log2_size` in `[1..5]`, verifying every group across the full 64-lane launch. Doc: new rows in the `subgroup.md` Reductions/scans table; new per-op sections; the "removed" note is updated to drop `reduce_min` / `reduce_max` (now portable).
Implement a portable ballot operation that returns a u32 bitmask where bit i is set if lane i's predicate is non-zero. Works across CUDA (__ballot_sync), AMDGPU (amdgcn_ballot.i32), and SPIR-V/Vulkan (OpGroupNonUniformBallot). Follows the same cross-backend pattern as subgroup.shuffle: a single Python API (subgroup.ballot) dispatches to the appropriate backend intrinsic at codegen time. On AMDGPU CDNA with 64-wide wavefronts only the low 32 bits are returned, consistent with the u32 return type.
Mac OS X build was failing because spirv_codegen.cpp was accessing IRBuilder::t_v4_uint_ directly, which is a private member. Add a public v4_u32_type() accessor following the existing pattern (u32_type(), bool_type(), etc.) and use it from the ballot lowering.
Per-lane inclusive sum scoped to 2**log2_size lanes, where every lane with head_flag != 0 resets the running sum. Useful for stream compaction and sparse / variable-length records. Implementation: one subgroup.ballot(head_flag != 0) to materialise a u32 of head positions, then a Hillis-Steele inclusive sum bounded by `distance >= offset` (distance = lane - segment_head, segment_head from 31 - clz(effective_mask & ((1 << (lane + 1)) - 1)) with a virtual head OR-injected at group_base so lower is always non-zero). Cost: 1 ballot + 1 clz + log2_size shuffles + log2_size adds, fully unrolled. Same shape as inclusive_add with a single-instruction setup. Tests: parametrized over the standard dtypes (i32 / i64 / u64 / f32 / f64) and log2_size in [0..5], plus three contract tests (no head flags -> equivalent to inclusive_add; every lane is a head -> output equals input; truthy non-binary head_flag values). Doc: new row in the Reductions/scans table; new per-op section after reduce_all_min / reduce_all_max.
`qd.clz(u32_value)` was emitting QD_NOT_IMPLEMENTED on CUDA and produced undefined results on SPIR-V (GLSL.std.450 FindSMsb is undefined for the all-bits-set case). The new `subgroup.segmented_reduce_add` is the first user of `clz` in the codebase and exposed both bugs. * CUDA: route u32 / u64 inputs through the same `__nv_clz` / `__nv_clzll` intrinsics used for i32 / i64 — the underlying bit pattern is what matters, the C declaration on signed types is a header-level convention. * SPIR-V: dispatch to FindUMsb (#75) for unsigned inputs and FindSMsb (#74) for signed. The two GLSL.std.450 instructions return a value of the same type as their operand, so add an explicit OpBitcast back to i32 before the `32 - msb - 1` subtraction (otherwise SPIR-V's strict-type `sub` asserts on mixed i32 / u32). * Python: in `segmented_reduce_add`, wrap `clz`'s result in `i32(...)` so the subsequent arithmetic is uniformly signed-32-bit (the trace- time tracer would otherwise propagate u32 from the input through to the subtraction, hitting SPIR-V's same-type assertion). Tests: `subgroup.segmented_reduce_add` tests now pass on CUDA + Vulkan across i32 / i64 / u64 / f32 / f64 and `log2_size` in [0..5], including the all-heads, no-heads, and truthy-predicate edge cases.
hughperkins
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May 15, 2026
| def _is_apple_gpu_backend(): | ||
| """Metal or MoltenVK (Vulkan-on-Darwin).""" | ||
| arch = qd.lang.impl.current_cfg().arch | ||
| if arch == qd.metal: |
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return arch == qd.metal or (arch == qd.vulkan and platform.system() == "Darwin")
hughperkins
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May 15, 2026
| return False | ||
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| def _skip_if_radix_sort_large_n_on_apple_gpu(N): |
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why are we skipping large n on apple gpu?
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May 15, 2026
| # off-by-one tile (B0 ends mid-block), three-pass recursion. Default 5 MB | ||
| # scratch holds N + ceil(N/256) + ... <= ~1.3M u32 slots, so the largest | ||
| # size below (200_000) fits comfortably with ~780-slot partials. | ||
| _SELECT_SIZES = [1, 7, 255, 256, 257, 1023, 1024, 1025, 65536, 65537, 200_000] |
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lets move all these various globals to the top of the module
hughperkins
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May 15, 2026
| rtol = 2e-5 * math.sqrt(N) | ||
| assert rtol <= 1e-3 or N > 100, f"f32 scan rtol={rtol:g} too loose for small N={N}" | ||
| assert rtol <= 1e-2 or N > 100_000, f"f32 scan rtol={rtol:g} too loose for medium N={N}" | ||
| atol = 1e-3 |
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lets move all definitions or calculations of rtol or atol to the top of the module
- global constants as global constnats
- formula as reusable formula for atol and rtol
…onstants - Consolidate dtype-support helpers to a single source of truth. ``_unsupported_dtype_reason(dtype) -> str | None`` replaces the previous bool/skip pair; ``_skip_if_dtype_unsupported`` is a thin wrapper for the parametrized-test path; the in-loop call site (``test_device_reduce_min_derives_identity_from_dtype``) reads the reason directly to ``continue`` past unsupported dtypes. - Document the dtype-support matrix as a structured arch x platform table comment so it can be eyeballed without parsing predicate logic. - ``_is_apple_gpu_backend`` collapsed to a single-line return. - ``_skip_if_radix_sort_large_n_on_apple_gpu`` docstring now states *why* we're skipping (observed correctness gap above N >= 200_000 on Metal / MoltenVK; smaller N passes cleanly; CUDA / AMDGPU / Linux Vulkan unaffected; tracked as a follow-up). - All scattered module globals (``_REDUCE_SIZES``, ``_SCAN_SIZES``, ``_SELECT_SIZES``, ``_SELECT_STRUCT_SIZES``, ``_SELECT_STRUCT_NFIELDS``, ``_RADIX_SORT_SIZES``, ``_RBK_SIZES``, ``_TINY_SCRATCH_BYTES``, ``_REDUCE_DTYPES``, ``_SCAN_DTYPES``, ``_SELECT_DTYPES``, ``_RADIX_KEY_DTYPES``, ``_DTYPE_TO_NP``, ``_MIN_IDENTITY``, ``_MAX_IDENTITY``) are now declared in a single section at the top of the module instead of being interleaved with test definitions. - All scattered rtol/atol literals are now expressed as named constants (``_F32_REDUCE_*``, ``_F32_LARGE_N_*``, ``_F64_*``) plus a reusable ``_f32_scan_tol(N)`` formula at the top of the module, with the error model and the contract assertions documented in one place. Call sites use the constants/formula instead of inline literals. No tolerance values changed; this is a reorganization only.
…to 120c The line-wrapping CI check on PR 693 flagged the top-of-module docstring at ~78c, which was the legacy AI-default wrap width. Since this is a wholly-new file in the PR, every line counts as 'added' for the diff-only linter. Reflowed the top docstring + four short test docstrings that were still at ~70-80c so they use the project's 120c target. No semantic changes.
Continuing the 120c reflow from b313341. The CI line-wrapping check flags 3 violations at a time, so this is the second pass clearing candidate runs across: - llvm_context.cpp:756 (NVPTX64 datalayout comment block) - _algorithms.py (PrefixSumExecutor deprecation note) - _radix_sort.py (3 docstring/comment runs) - _reduce.py (2 docstring runs) - _reduce_by_key.py (3 docstring/comment runs) - _scan.py (4 docstring/comment runs) - algorithms.md (radix-sort indices example comment) No semantic changes; pure reflow.
| ``qd.types.struct(...)`` - e.g. the libuipc ``Vector{2,3,4}i`` shapes). The scatter is | ||
| ``dst[idx] = src[i]``, which lowers per-field for struct dtypes, so no scratch reinterpretation is | ||
| needed for wider / composite element types. | ||
| flags: 1-D ``i32`` tensor, same shape as ``arr``. Each entry is treated as a boolean (``!= 0`` selects). |
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The docstring says != 0 selects, but the implementation prefix-sums the raw i32 flag values as counts — so flags = [2, 0, 1] would produce scanned indices [0, 2, 2], giving wrong output and num_out = 3 instead of 2.
Suggestion: tighten the contract to require strictly 0/1 flags and document it as such (both here and in algorithms.md). No need to add a normalization pass — just make it the caller's responsibility.
Proposed wording for the flags arg:
Every entry must be exactly
0or1(1selects). Non-0/1 values produce incorrect results. Caller-built — populate with a kernel applying your predicate, writing1for selected and0otherwise.
Same update needed in algorithms.md (overview table + constraints bullet).
| f"({cap * 4} bytes). Call quadrants._scratch.set_scratch_bytes(...) " | ||
| f"before any algorithm runs to raise the cap. For N=1M expect to " | ||
| f"need ~5 MB; for N=10M ~50 MB." | ||
| ) |
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This capacity check only accounts for one level of scan partials (hist_len + ceil(hist_len / 256)), but _exclusive_scan_inplace_u32(..., n=hist_len, partials_cursor=hist_len) recursively needs deeper levels too (e.g. + ceil(ceil(hist_len/256)/256) and so on).
If a caller sets scratch to exactly the size reported here for a large signed/f32 sort, the later recursive scan check raises after _twiddle_pass has already transformed keys in place, leaving the user's data corrupted with no way to recover.
Suggestion: compute the full recursive scan footprint before accepting the call. Something like:
def _scan_total_scratch(n: int, partials_cursor: int) -> int:
total = partials_cursor
while n > BLOCK_DIM:
B = (n + BLOCK_DIM - 1) // BLOCK_DIM
total = partials_cursor + B
partials_cursor = total
n = B
return totalThen use needed = _scan_total_scratch(hist_len, hist_len) here, and crucially this check already runs before _twiddle_pass which is correct — just the footprint calculation needs the recursive accounting.
The implementation prefix-sums `flags` directly as counts, so any non-0/1 entry silently breaks the index / num_out math (a stray `2` advances the destination cursor by 2). Document the contract as 0/1-only in both the docstring and algorithms.md; no implicit normalization pass - normalization is the caller's responsibility (matches CUB / Thrust stream-compaction conventions).
Adds ``_scan_total_scratch_slots(n, partials_cursor)`` to ``_scan.py``: walks the level-by-level scan recursion (n -> ceil(n/BLOCK_DIM) until <= BLOCK_DIM) and returns the high-water-mark scratch slot index. Uses it in two places that previously only counted *one* level of partials and so accepted budgets that the recursion later rejected mid-call: - ``device_radix_sort``: critical, because ``_twiddle_pass`` mutates the user's signed-int / float keys in place *after* the scratch check. With the single-level estimate, a budget that's just barely too small slipped past the check, twiddle ran, then the recursive scan raised, leaving the caller with bit-XOR'd keys and no recovery path. The check now refuses the call before any side effect runs. - ``device_exclusive_scan_*`` driver: same logic, less impact (no in-place mutation of the user's input), kept for symmetry / clearer up-front error. Internal recursion-time check inside ``_exclusive_scan_inplace_*`` stays as a defensive backstop; the new helper is the contract that outer drivers honour first.
…ort recursive-scratch check Two focused regressions for the PR 693 review issues: - ``test_device_select_zero_one_flag_contract``: pins the 0/1 contract by construction (interleaved ``[1,0,1,0,...]`` selects exactly N/2 even-index elements). If a future change breaks the prefix-sum-as-count semantics or re-introduces an implicit normalization, this test is the canary. - ``test_device_radix_sort_recursive_scratch_check_keys_unchanged``: picks a scratch budget in the (single-level-pass, full-recursion-fail) window and asserts that a refused call leaves the user's signed-int keys byte-identical to the original (i.e. ``_twiddle_pass`` did NOT run before the error). This test would have failed against the pre-fix single-level estimate and passes against the new ``_scan_total_scratch_slots``-based check. Both pass on CUDA and Vulkan locally.
# Conflicts: # docs/source/user_guide/algorithms.md # docs/source/user_guide/decompositions.md # docs/source/user_guide/subgroup.md # python/quadrants/algorithms/_algorithms.py # python/quadrants/lang/simt/reductions.py # python/quadrants/lang/simt/subgroup.py # tests/python/test_simt.py
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* [Misc] Warn user to disable caching when print_ir/QD_DUMP_IR enabled (Genesis-Embodied-AI#425) Co-authored-by: v01dxyz <v01dxyz@v01d.xyz> * [Build] Pin torch version to CUDA 12.8 for CUDA tests (Genesis-Embodied-AI#428) * [Misc] Fixing up taichi-dev urls (Genesis-Embodied-AI#429) * [Perf] Rename cuda_graph to gpu_graph across the codebase (Genesis-Embodied-AI#430) * Misc: fix typo integeral -> integral (Genesis-Embodied-AI#434) Co-authored-by: v01dxyz <v01dxyz@v01d.xyz> * [Perf] CUDA graph 4: call from multiple locations (Genesis-Embodied-AI#420) * [Bug] Fix fastcache not restoring graph_do_while_arg (Genesis-Embodied-AI#435) * [Perf] Cache last-call result in perf_dispatch for single-compatible case (Genesis-Embodied-AI#438) * Fix gpu_graph fallback on old Nvidia GPU. (Genesis-Embodied-AI#443) * Fix shared memory offset not reset between CUDA kernels. (Genesis-Embodied-AI#442) * [Misc] Allow disabling GPU graph via QD_GPU_GRAPH=0 env var (Genesis-Embodied-AI#439) * [Misc] Add named top-level loops (Genesis-Embodied-AI#440) * [Misc] Rename gpu_graph to graph (Genesis-Embodied-AI#446) * [Misc] Add cross-platform shuffle (Genesis-Embodied-AI#447) * [Bug] Fix graph_do_while on Windows: search for cudadevrt.lib (Genesis-Embodied-AI#456) * [Bug] Also search default CUDA toolkit install location on Windows (Genesis-Embodied-AI#461) * [SPIRV] Feature Parity Atomics & Shared Array (Genesis-Embodied-AI#432) * [Misc] Change clang format to 120 characters (Genesis-Embodied-AI#463) * [Misc] CUDA graph 5 Add fatbin (Genesis-Embodied-AI#464) * [Bug] Reuse VkInstance across init/reset cycles (Genesis-Embodied-AI#465) * [Perf] Tiles 1: _load, _store, _eye_ (Genesis-Embodied-AI#466) * [Misc] Remove dead InternalFuncStmt type_check override (Genesis-Embodied-AI#471) * [Perf] Tiles 2: add cholesky and ger (Genesis-Embodied-AI#472) * [Perf] Tiles 2b: add triangular solve (Genesis-Embodied-AI#474) * [Misc] Refactor: use _get_col/_set_col in tiles load/store/init (Genesis-Embodied-AI#475) * [Build] Fix flaky test_clock_accuracy (Genesis-Embodied-AI#436) * Fix AARCH64 emitting invalid asm in CUDA kernels. (Genesis-Embodied-AI#473) Co-authored-by: Hugh Perkins <hughperkins@gmail.com> * [AMDGPU] Enable HIP memory pool and surface pool-exhaustion errors. (Genesis-Embodied-AI#485) * [AMDGPU] Scope hsaco tmp dir per-user to avoid collisions. (Genesis-Embodied-AI#484) * [Perf] Tiles 3: Add slice syntax, qd.outer() and initial doc (Genesis-Embodied-AI#477) * [AMDGPU] Fix gradient computation. (Genesis-Embodied-AI#486) * Enable all backends that are supported in unit tests. (Genesis-Embodied-AI#488) * Fix SPIRV ID overflow for large kernels due to autodiff. (Genesis-Embodied-AI#489) * [Misc] Fix purity checker to allow accessing constants from quadrants modules (Genesis-Embodied-AI#487) * [Misc] Increase tolerance for clock monotonic test (Genesis-Embodied-AI#492) * [CI] Serialize api doc workflow (Genesis-Embodied-AI#494) * [CI] Increase tolerance for clock test (Genesis-Embodied-AI#506) * [CI] Increase clock test tolerance to 20% (Genesis-Embodied-AI#509) * [Perf] Add tensor_type parametrization to tile16 tests (Genesis-Embodied-AI#504) * [Perf] Tiles 4b: Migrate tiles16 tests to enable fastcache (Genesis-Embodied-AI#505) * [Perf] Tiles 4c: add Tiles16x16 proxy (Genesis-Embodied-AI#507) * [Perf] Tiles 4d: Consolidate slice error tests using parametrize (Genesis-Embodied-AI#508) * [Perf] Tiles 4: add SharedArray slice support (Genesis-Embodied-AI#482) * [Perf] Tiles 5: add Cholesky benchmark demo (Genesis-Embodied-AI#483) * [Doc] Add user guide page for subgroup shuffle (Genesis-Embodied-AI#512) * [Perf] Implement cross-platform shuffle_down (Genesis-Embodied-AI#510) * [Perf] Add portable subgroup reduce_add and reduce_all_add (Genesis-Embodied-AI#511) * [Perf] Add first warmup config to perf dispatch (Genesis-Embodied-AI#422) * [AutoDiff] Autodiff 1: Add baseline adstack regression test for unary_collections (Genesis-Embodied-AI#500) * [AutoDiff] Autodiff 2: Implement derivative for tan (Genesis-Embodied-AI#501) * [AutoDiff] Autodiff 3: Recompute tanh/exp on the operand in the reverse pass (Genesis-Embodied-AI#502) * [AutoDiff] Autodiff 4: Mark rsqrt as non-linear for adstack promotion (Genesis-Embodied-AI#503) * [AutoDiff] Autodiff 5: Fix adjoint-alloca placement for GlobalLoads outside the current range-for (Genesis-Embodied-AI#496) * [AutoDiff] Autodiff 6: Adstack regression tests (Genesis-Embodied-AI#491) * [AutoDiff] Autodiff 7: Fix header size in AdStackAllocaStmt to match u64 runtime layout (Genesis-Embodied-AI#534) * [AutoDiff] Autodiff 8: Surface LLVM adstack push/pop overflow as a Python exception (Genesis-Embodied-AI#535) * [AutoDiff] Autodiff 9: Guard against LLVM worker-thread stack overflow from large per-task adstack budget (Genesis-Embodied-AI#495) * [AutoDiff] Autodiff 10: Implement adstack for SPIR-V (Genesis-Embodied-AI#490) * [AutoDiff] Autodiff 11: Latent adstack-adjacent fixes (AMDGPU hipFree, flush() keeps ctx_buffers_, always-preallocate) (Genesis-Embodied-AI#536) * [Doc] Add AGENTS.md with instructions for AI agents (Genesis-Embodied-AI#541) * [Bug] Abort kernel execution on assertion failure instead of segfaulting (Genesis-Embodied-AI#419) * [Type] ndarray typing 1: Add eval_str=True to inspect.signature() calls (Genesis-Embodied-AI#411) * [CI] Suppress reportPrivateImportUsage in torch-using files (Genesis-Embodied-AI#552) * [Misc] QD_DUMP_IR dumps to files with the task_id added to the filename (Genesis-Embodied-AI#441) * [Type] ndarray typing 2: Fix NDArray single-arg subscript crash (Genesis-Embodied-AI#412) * [Test] Flush xdist channel before worker exit so test failure reports are visible (Genesis-Embodied-AI#555) * [CI] Reduce test retries on CI from 3 to 1. (Genesis-Embodied-AI#554) * [AutoDiff] Autodiff 12: Heap-backed adstack on LLVM backends (CPU/CUDA/AMDGPU) (Genesis-Embodied-AI#537) * [AutoDiff] Autodiff 13: Heap-backed adstack on SPIR-V backends (Metal, Vulkan) (Genesis-Embodied-AI#493) * [AutoDiff] Autodiff 14: Resolve bounded-inner-loop adstacks without default_ad_stack_size fallback (Genesis-Embodied-AI#539) * [SPIRV] Vulkan SPIR-V correctness: atomic-view aliasing, PSB stride, narrow storage caps, u1 cast, per-init layer recheck (Genesis-Embodied-AI#513) * [Build] Autodiff 15: Replace 2022 MoltenVK pin with LunarG Vulkan SDK fetch and sanitise MoltenVK cap advertisement (Genesis-Embodied-AI#551) * [Test] Suppress stock pytest-timeout to avoid conflict with pytest_hardtle (Genesis-Embodied-AI#557) * [Vulkan] Use SDK validation layer for debugPrintf instead of apt package (Genesis-Embodied-AI#562) * [Test] Fix flaky perf_dispatch tests by increasing work amounts (Genesis-Embodied-AI#559) * [Test] Add --maxfail CLI option to run_tests.py (default 20) (Genesis-Embodied-AI#558) * [CI] Vulkan debug printf fix to address flaky tests (Genesis-Embodied-AI#563) * [Docs] Add a new page to help for first time contributors (Genesis-Embodied-AI#426) Authored-by: v01dxyz <v01dxyz@v01d.xyz> * [AutoDiff] Autodiff 16: Resolve reverse-mode adstack depths per-launch via runtime-evaluated SizeExpr (Genesis-Embodied-AI#543) * Fix: raise error if device memory allocation fails (Genesis-Embodied-AI#451) (Genesis-Embodied-AI#453) Co-authored-by: v01dxyz <v01dxyz@v01d.xyz> Co-authored-by: Hugh Perkins <hughperkins@gmail.com> * [CI] Add CI job to check line wrapping of comments and docs (Genesis-Embodied-AI#564) * [Misc] Add coverage report to PRs, including kernels (Genesis-Embodied-AI#470) * [CI] CI wrap check feeds only diffs to agent (Genesis-Embodied-AI#567) * Skip 'flaky' test on MacOS CI. (Genesis-Embodied-AI#573) * [Test] Fix missing `import sys` in test_fail_device_memory_allocation (Genesis-Embodied-AI#574) * [CI] Fix Vulkan debugPrintf flake with session-scoped warmup (Genesis-Embodied-AI#571) * [AutoDiff] determine_ad_stack_size: replace whole-CFG Bellman-Ford with SCC + DAG DP (Genesis-Embodied-AI#575) * [Test] Fix macOS OOM skip reason to describe actual root cause (Genesis-Embodied-AI#576) * [Lang] whole_kernel_cse: 2.5x compile time speedup on large kernels (Genesis-Embodied-AI#577) * [CI] Add CI check for unnecessarily deleted comments (Genesis-Embodied-AI#570) * [CI] Migrate coverage report to github Check page (Genesis-Embodied-AI#566) * [Lang] Skip IR verifier between passes unless debug=true (Genesis-Embodied-AI#579) * [Lang] Inline AdStack ops on release LLVM codegen: dramatically reduces compile time for adstack-enabled reverse-mode kernels (Genesis-Embodied-AI#584) * [CUDA] Honor offline_cache=False end-to-end so QD_OFFLINE_CACHE=0 actually gives a cold compile (Genesis-Embodied-AI#580) * [Type] Tensor 24 (Genesis-Embodied-AI#561) Co-authored-by: hugh <hugh@slurm-login-0.slurm-login.tenant-slurm.svc.cluster.local> * [Lang] auto_diff host-walk reductions: dramatically faster front-end compile time on adstack-enabled reverse-mode kernels (Genesis-Embodied-AI#587) * [AutoDiff] Speed up reverse-mode kernel launches on GPU backends (Genesis-Embodied-AI#578) * [Vulkan] Move adstack-sizer scratch out of Function-scope memory to fix SPIR-V pipeline build failures (Genesis-Embodied-AI#588) * [AutoDiff] Improve diagnosis of unsupported reverse-mode AD patterns (Genesis-Embodied-AI#590) * [Bug] Fix: promote Ndarray to AnyArray in build_Name for flattened struct fields (Genesis-Embodied-AI#592) * [SPIR-V] Shrink reverse-grad kernel MSL by ~50% (Genesis-Embodied-AI#591) * [CI] Add CI check that PR changes have test coverage (Genesis-Embodied-AI#596) * [Perf] Enable zero-copy in to_torch() and to_numpy() (Genesis-Embodied-AI#450) * Add BufferView: safe sub-range ndarray access for kernels (Genesis-Embodied-AI#585) Co-authored-by: alanray-tech <alanray-tech@users.noreply.github.com> Co-authored-by: Hugh Perkins <hughperkins@gmail.com> * [Doc] Add user-facing fastcache documentation (Genesis-Embodied-AI#597) Co-authored-by: hugh <hugh@slurm-login-0.slurm-login.tenant-slurm.svc.cluster.local> * [Misc] Upgrade to enable v1 dlpack so to_numpy(copy=False) writable (Genesis-Embodied-AI#598) Co-authored-by: root <root@rtx-209-201.slurm-compute.tenant-slurm.svc.cluster.local> * [AutoDiff] Cut reverse-mode adstack memory usage 10x on all backends (Genesis-Embodied-AI#599) * [Misc] Add CI check for feature file factorization (Genesis-Embodied-AI#606) * [Perf] Skip _recursive_set_args for all-Field frozen dataclass structs (Genesis-Embodied-AI#607) Co-authored-by: Cursor <cursoragent@cursor.com> * [AutoDiff] SNode-arm bound-expr capture rejects fold-attack gate indices (Genesis-Embodied-AI#610) * [Misc] Suppress field fastcache warning for qd.Tensor (Genesis-Embodied-AI#615) Co-authored-by: Cursor <cursoragent@cursor.com> * [AutoDiff] Adstack heap: clip reducer count by per-task loop trip count (compile-time and SizeExpr-evaluated) (Genesis-Embodied-AI#611) * [Misc] Forward copy= through qd.Tensor, add copy=None option (Genesis-Embodied-AI#616) Co-authored-by: Cursor <cursoragent@cursor.com> * [Doc] Update README (Genesis-Embodied-AI#617) Co-authored-by: Cursor <cursoragent@cursor.com> * [CI] Fix coverage report showing def lines as uncovered (Genesis-Embodied-AI#623) Co-authored-by: Cursor <cursoragent@cursor.com> * [Perf] Generic launcher: persistent context, JIT-pointer reuse, Metal compute encoder, LLVM-GPU async memory ops (Part 1/2) (Genesis-Embodied-AI#619) * [CI] Encode Python-first testing policy in coverage-check prompt (Genesis-Embodied-AI#622) Co-authored-by: Cursor <cursoragent@cursor.com> * [CI] Add PR Line change report (Genesis-Embodied-AI#624) Co-authored-by: Cursor <cursoragent@cursor.com> * [CI] Disable quadrants pytest plugin during quadrants internal coverage runs (Genesis-Embodied-AI#629) Co-authored-by: Cursor <cursoragent@cursor.com> * [AutoDiff] Adstack load+store eliminations: EliminateRecomputableAdStackPushes pass + leaf extensions (Genesis-Embodied-AI#621) * [CI] Simplify coverage PR comment to a single linked line (Genesis-Embodied-AI#630) * [CUDA] Add AGX Thor, SM_110 (Genesis-Embodied-AI#631) Co-authored-by: Johnny Nunez and Hugh Perkins * [CI] Lines changed report: collapse PR comment to a single linked totals line (Genesis-Embodied-AI#632) * [FEATURE] Support external Metal command queue via qd.init (Genesis-Embodied-AI#618) Co-authored-by: Cursor <cursoragent@cursor.com> * [Perf] Cache adstack-sizer metadata per task across SPIR-V + LLVM-GPU; per-snode / DeviceAllocation invalidation (Part 2/2) (Genesis-Embodied-AI#620) * [AutoDiff] Disable EliminateRecomputableAdStackPushes pending mutated-SNode chain-leaf fix (Genesis-Embodied-AI#633) * [AutoDiff] Adstack chain-clone safety: mutated-SNode leaf reject + load_top consumer-aware guard (Genesis-Embodied-AI#634) * [Docs] Add user-guide page for qd.simt.block.* primitives (Genesis-Embodied-AI#638) * [Docs] Expand qd.simt.subgroup user-guide page to cover every op (Genesis-Embodied-AI#639) * [Perf] Streams 1-4 (Genesis-Embodied-AI#410) * [Docs] Add user-guide page for matrix decompositions and solvers (Genesis-Embodied-AI#643) * [Bug] Revert "[Perf] Streams 1-4 (Genesis-Embodied-AI#410)" (Genesis-Embodied-AI#650) * [Docs] Add user-guide page for atomics and bit operations (Genesis-Embodied-AI#640) * [Docs] Add user-guide page for qd.simt.grid.* primitives (Genesis-Embodied-AI#641) * [AutoDiff] Adstack max-reducer: parallel multi-axis MaxOverRange dispatch (Genesis-Embodied-AI#635) * [AMDGPU] Fix amdgpu parallel rand init (Genesis-Embodied-AI#658) * [Perf] Adstack: skip max-reducer recognizer on CPU + lift host-eval cap (Genesis-Embodied-AI#655) * [Perf] Re-land Streams 1-4 with bug fixes (Genesis-Embodied-AI#653) * [AMDGPU] Apply device_memory_GB=0.3 cap to AMDGPU tests (Genesis-Embodied-AI#659) * [Perf] Per-launch host sync: drop wait_idle on SPIR-V, pin stream and drop stream_synchronize on CUDA/AMDGPU (Genesis-Embodied-AI#654) * [AMDGPU] Unload hipModule_t in JITModuleAMDGPU destructor (Genesis-Embodied-AI#660) * [AMDGPU] Trim default mempool on qd.reset() (Genesis-Embodied-AI#669) * [AMDGPU] Hoist rand-state buffer to process lifetime (Genesis-Embodied-AI#668) * [Streams] Use events for streams serialization on AMDGPU and CUDA (Genesis-Embodied-AI#667) * [Perf] Adstack max-reducer: launch cache + zero-copy result map; content-stable registry_id (Genesis-Embodied-AI#671) * [SPIR-V] dispatch_max_reducers: register each task with the real kernel name (Genesis-Embodied-AI#675) * [AutoDiff] Debug-mode field/grad/dual: dtype, layout, and access-time invariants (Genesis-Embodied-AI#677) * [Docs] Add user-guide page for qd.algorithms.* device-wide algorithms (Genesis-Embodied-AI#642) Co-authored-by: alanray-tech <alan.ray@genesis-ai.company> * [Docs] Doc for existing atomics: switch support table to per-backend columns (Genesis-Embodied-AI#657) Co-authored-by: alanray-tech <alan.ray@genesis-ai.company> * [GPU] Cross gpu atomics (Genesis-Embodied-AI#666) Co-authored-by: alanray-tech <alan.ray@genesis-ai.company> * [GPU] Make block operations portable cross-gpu (Genesis-Embodied-AI#664) * [Perf] CPU LLVM adstack-cache: skip per-launch bump-writes + ndarray_shapes capture on forward-only handles (Genesis-Embodied-AI#685) * [GPU] Cross-GPU for grid ops (Genesis-Embodied-AI#670) * [Math] Make bitop operations portable cross-gpu (Genesis-Embodied-AI#662) * [AMDGPU] Always use wave64, on both RDNA and CDNA (Genesis-Embodied-AI#687) * [AMDGPU] Use syncscope("agent") for atomix xor to avoid CAS livelock (Genesis-Embodied-AI#672) * [GPU] New bit ops for QIPC (Genesis-Embodied-AI#679) * [GPU] Subgroup ops cross-gpu (Genesis-Embodied-AI#665) * [Graph] Rename CUDA Graph to Graph in docs (Genesis-Embodied-AI#691) * [SPIR-V] Fix FIFO-queue ordering when sharing command queue. (Genesis-Embodied-AI#694) * [Atomics] New QIPC ops for atomics (Genesis-Embodied-AI#690) * Pass dataclass sub-structs into qd.func (Genesis-Embodied-AI#698) * [AMDGPU] HIP graph runtime support for @qd.kernel(graph=True) (Genesis-Embodied-AI#692) * [CI] Add per-file timing report to Mac Metal test job (Genesis-Embodied-AI#695) Co-authored-by: Cursor <cursoragent@cursor.com> * [CI] Enable kernel disk cache during tests (Genesis-Embodied-AI#696) * [Math] New QIPC ops for single-threaded linalg (Genesis-Embodied-AI#683) * [BREAKING][GPU] New QIPC ops for subgroups (Genesis-Embodied-AI#676) * [GPU] New QIPC ops for block (Genesis-Embodied-AI#684) * [GPU] New device-level ops for QIPC (Genesis-Embodied-AI#693) * [algorithms] PrefixSumExecutor: drop unused GRID_SZ local (Genesis-Embodied-AI#701) * [block] sync(): fix unsupported-arch error message (Genesis-Embodied-AI#700) * [volatile_load] add qd.volatile_load primitive (closes Genesis-Embodied-AI#648) (Genesis-Embodied-AI#702) * [AutoDiff] Reject recycled identity_key in AdStackCache::register_adstack_sizing_info (Genesis-Embodied-AI#708) * [Vulkan] Declare GroupNonUniform SPIR-V caps and enable shaderSubgroupExtendedTypes (Genesis-Embodied-AI#707) * Fix duplicate HIP graph driver-function declarations after v1.0.0 merge The amd-integration fork had cherry-picked the HIP graph driver functions (graph_create / graph_destroy / graph_add_kernel_node / graph_instantiate / graph_exec_destroy / graph_launch), and upstream v1.0.0 added the same set. The per-file 3-way merge appended both copies into amdgpu_driver_functions.inc.h, producing redeclaration errors that broke the AMDGPU RHI/runtime compile. Drop the upstream duplicate block; the signatures are identical to the fork's existing declarations. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix AMDGPU launcher coherence and num_instructions visibility after v1.0.0 merge - kernel_launcher.cpp: the 3-way merge spliced upstream v1.0.0's launch_llvm_kernel rewrite (ephemeral arg/context buffers, explicit-stream path, AmdgpuDefaultStream PinGuard) onto the AMD fork's kernarg-by-value + persistent-scratch design, leaving references to undefined `ephemeral_context_ptr`. Restore the fork's coherent launch_llvm_kernel verbatim; it calls the (already merged) enhanced launch_offloaded_tasks, which keeps the max-reducer dispatch and stream-parallel groups adapted onto the AMD launch path. - llvm_context.h: both the fork and upstream added `num_instructions`; the merge kept upstream's private placement, but the AMDGPU codegen force-inline heuristic calls it statically from outside the class. Move it back to the public section. Co-authored-by: Cursor <cursoragent@cursor.com> * Restore async result D2H and hoist kernarg vectors in AMDGPU launcher The v1.0.0 merge resolution regressed two amd-integration baseline optimizations in launch_llvm_kernel / launch_offloaded_tasks: - The per-launch result-buffer copy was a blocking memcpy_device_to_host, forcing a host stall on every value-returning launch and serializing the GPU pipeline. Restore the async D2H (the caller synchronizes lazily when it needs the value); external-array transfers still stream_synchronize once before reading back. - launch_task constructed the kernarg std::vectors from initializer lists ({kernarg_payload} / {kernarg_size}) on every dispatch (heap alloc + free per launch). Hoist arg_ptrs/arg_sizes out of the per-task launch and reuse. Co-authored-by: Cursor <cursoragent@cursor.com> * amdgpu: default to LDS permlane64 emulation; drop host-x86 barrier asm on retarget Two AMDGPU JIT-compile crashes surfaced after the v1.0.0 merge pulled in the QIPC subgroup ops (Genesis-Embodied-AI#676), which made the rigid constraint solver's wave-cooperative reductions route through `amdgpu_cross_half_shuffle_i32`. Both manifested as a SIGSEGV inside `llvm::SIInstrInfo::getInstSizeInBytes` during `JITSessionAMDGPU::compile_module_to_hsaco` (i.e. at first kernel launch), and reproduce on gfx942 / MI300X. Baseline 0.4.6 never emitted these constructs, which is why it was unaffected. 1. Native `llvm.amdgcn.permlane64` lowering crashes the bundled LLVM 22.1.0 AMDGPU backend. Default `amdgpu_permlane64` to the existing LDS-roundtrip software emulation on every target (it produces identical results). Add `QD_AMDGPU_USE_NATIVE_PERMLANE64=1` to opt back into the native instruction once the backend bug is fixed; the old `QD_AMDGPU_FORCE_PERMLANE64_FALLBACK` is now the default and still honored. This is the actual crash fix. 2. The runtime module is compiled by the host x86_64 clang and only retargeted to amdgcn here, so `amdgpu_cross_half_shuffle_i32`'s `__asm__ volatile("" : "+v"(byte))` optimization barrier carries x86 flag clobbers (`~{dirflag},~{fpsr},~{flags}`) that are meaningless on AMDGPU. The IR verifies but the empty-body INLINEASM is invalid on the amdgcn target. Neutralize empty-body barrier asm during retarget (forward the tied value, then erase) so no stale host asm reaches codegen. On the wave64 targets we ship `ds_bpermute` already addresses the full wave, so the hint is a no-op. Co-authored-by: Cursor <cursoragent@cursor.com> * style: apply clang-format (v19.1.7) to AMDGPU fn_attrs and launcher sources CI pre-commit's clang-format hook reformatted these files (long declarations/lambda signatures collapsed onto single lines per the repo's clang-format config). Apply the same formatting so the hook passes. No functional changes. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(amdgpu): use CreateNeg for branchless i32 sgn instead of CreateSub(0, input) clang-tidy (modernize-use-nullptr, -warnings-as-errors) flagged `builder->CreateSub(0, input)` in the i32 sgn path: the literal `0` binds to the `llvm::Value*` LHS parameter as a null pointer, not an integer zero. Replace with `builder->CreateNeg(input)`, which emits `0 - input` with a proper zero constant -- identical intended semantics, and clang-tidy clean. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Robert Dazi <14996868+v01dXYZ@users.noreply.github.com> Co-authored-by: v01dxyz <v01dxyz@v01d.xyz> Co-authored-by: Hugh Perkins <hughperkins@gmail.com> Co-authored-by: Alexis DUBURCQ <alexis.duburcq@gmail.com> Co-authored-by: hugh <hugh@slurm-login-0.slurm-login.tenant-slurm.svc.cluster.local> Co-authored-by: alanray-tech <alan.ray@genesis-ai.company> Co-authored-by: alanray-tech <alanray-tech@users.noreply.github.com> Co-authored-by: root <root@rtx-209-201.slurm-compute.tenant-slurm.svc.cluster.local> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Johnny <johnnynuca14@gmail.com>
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