From fc81a8f8cc147bf4ed377636d6a6220ac99e3438 Mon Sep 17 00:00:00 2001
From: Yevhenii Havrylko <yhavrylko@nvidia.com>
Date: Fri, 24 Oct 2025 12:09:58 -0700
Subject: [PATCH 01/10] Add arch specific target support

---
 numba_cuda/numba/cuda/codegen.py        |  7 ++-
 numba_cuda/numba/cuda/cudadrv/driver.py |  2 +-
 numba_cuda/numba/cuda/cudadrv/nvrtc.py  | 83 ++++++++++++++++---------
 3 files changed, 58 insertions(+), 34 deletions(-)

diff --git a/numba_cuda/numba/cuda/codegen.py b/numba_cuda/numba/cuda/codegen.py
index 3ad26b360..7f5560779 100644
--- a/numba_cuda/numba/cuda/codegen.py
+++ b/numba_cuda/numba/cuda/codegen.py
@@ -203,7 +203,10 @@ def _ensure_cc(self, cc):
             return cc
 
         device = devices.get_context().device
-        return device.compute_capability
+        cc = device.compute_capability
+        if cc >= (9, 0):
+            cc = (cc[0], cc[1], "a")
+        return cc
 
     def get_asm_str(self, cc=None):
         cc = self._ensure_cc(cc)
@@ -333,7 +336,7 @@ def get_cufunc(self):
         cufunc = self._cufunc_cache.get(device.id, None)
         if cufunc:
             return cufunc
-        cubin = self.get_cubin(cc=device.compute_capability)
+        cubin = self.get_cubin()
         module = ctx.create_module_image(
             cubin, self._setup_functions, self._teardown_functions
         )
diff --git a/numba_cuda/numba/cuda/cudadrv/driver.py b/numba_cuda/numba/cuda/cudadrv/driver.py
index d15835557..3add758cf 100644
--- a/numba_cuda/numba/cuda/cudadrv/driver.py
+++ b/numba_cuda/numba/cuda/cudadrv/driver.py
@@ -2667,7 +2667,7 @@ def __init__(
         lto=None,
         additional_flags=None,
     ):
-        arch = f"sm_{cc[0]}{cc[1]}"
+        arch = f"sm_{cc[0]}{cc[1]}{cc[2]}"
         self.max_registers = max_registers if max_registers else None
         self.lineinfo = lineinfo
         self.cc = cc
diff --git a/numba_cuda/numba/cuda/cudadrv/nvrtc.py b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
index 8d861fcc1..23e3c6f62 100644
--- a/numba_cuda/numba/cuda/cudadrv/nvrtc.py
+++ b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
@@ -30,6 +30,42 @@ def _get_nvrtc_version():
     return (major, minor)
 
 
+def _verify_cc_tuple(cc):
+    version = _get_nvrtc_version()
+    ver_str = lambda version: ".".join(str(v) for v in version)
+
+    if len(cc) == 3:
+        cc, arch = (cc[0], cc[1]), cc[2]
+
+    if arch not in ("", "a", "f"):
+        raise ValueError(
+            f"Invalid architecture suffix '{arch}' in compute capability "
+            f"{ver_str(cc)}{arch}. Expected '', 'a', or 'f'."
+        )
+
+    supported_ccs = get_supported_ccs()
+    try:
+        found = max(filter(lambda v: v <= cc, [v for v in supported_ccs]))
+    except ValueError:
+        raise RuntimeError(
+            f"Device compute capability {ver_str(cc)} is less than the "
+            f"minimum supported by NVRTC {ver_str(version)}. Supported "
+            "compute capabilities are "
+            f"{', '.join([ver_str(v) for v in supported_ccs])}."
+        )
+
+    if found != cc:
+        found = (found[0], found[1], arch)
+        warnings.warn(
+            f"Device compute capability {ver_str(cc)} is not supported by "
+            f"NVRTC {ver_str(version)}. Using {ver_str(found)} instead."
+        )
+    else:
+        found = (cc[0], cc[1], arch)
+
+    return found
+
+
 def compile(src, name, cc, ltoir=False, lineinfo=False, debug=False):
     """
     Compile a CUDA C/C++ source to PTX or LTOIR for a given compute capability.
@@ -38,7 +74,8 @@ def compile(src, name, cc, ltoir=False, lineinfo=False, debug=False):
     :type src: str
     :param name: The filename of the source (for information only)
     :type name: str
-    :param cc: A tuple ``(major, minor)`` of the compute capability
+    :param cc: A tuple ``(major, minor)`` or ``(major, minor, arch)`` of the
+        compute capability
     :type cc: tuple
     :param ltoir: Compile into LTOIR if True, otherwise into PTX
     :type ltoir: bool
@@ -49,34 +86,18 @@ def compile(src, name, cc, ltoir=False, lineinfo=False, debug=False):
     :return: The compiled PTX or LTOIR and compilation log
     :rtype: tuple
     """
+    found = _verify_cc_tuple(cc)
     version = _get_nvrtc_version()
 
-    ver_str = lambda version: ".".join(str(v) for v in version)
-    supported_ccs = get_supported_ccs()
-    try:
-        found = max(filter(lambda v: v <= cc, [v for v in supported_ccs]))
-    except ValueError:
-        raise RuntimeError(
-            f"Device compute capability {ver_str(cc)} is less than the "
-            f"minimum supported by NVRTC {ver_str(version)}. Supported "
-            "compute capabilities are "
-            f"{', '.join([ver_str(v) for v in supported_ccs])}."
-        )
-
-    if found != cc:
-        warnings.warn(
-            f"Device compute capability {ver_str(cc)} is not supported by "
-            f"NVRTC {ver_str(version)}. Using {ver_str(found)} instead."
-        )
-
     # Compilation options:
     # - Compile for the current device's compute capability.
     # - The CUDA include path is added.
     # - Relocatable Device Code (rdc) is needed to prevent device functions
     #   being optimized away.
-    major, minor = found
+    major, minor = found[0], found[1]
+    cc_arch = found[2] if len(found) == 3 else ""
 
-    arch = f"sm_{major}{minor}"
+    arch = f"sm_{major}{minor}{cc_arch}"
 
     cuda_include_dir = get_cuda_paths()["include_dir"].info
     cuda_includes = [f"{cuda_include_dir}"]
@@ -140,7 +161,7 @@ def write(self, msg):
     return result, log
 
 
-def find_closest_arch(mycc):
+def find_closest_arch(cc):
     """
     Given a compute capability, return the closest compute capability supported
     by the CUDA toolkit.
@@ -150,17 +171,17 @@ def find_closest_arch(mycc):
     """
     supported_ccs = get_supported_ccs()
 
-    for i, cc in enumerate(supported_ccs):
-        if cc == mycc:
+    for i, supported_cc in enumerate(supported_ccs):
+        if supported_cc == cc:
             # Matches
-            return cc
-        elif cc > mycc:
+            return supported_cc
+        elif supported_cc > cc:
             # Exceeded
             if i == 0:
                 # CC lower than supported
                 msg = (
                     "GPU compute capability %d.%d is not supported"
-                    "(requires >=%d.%d)" % (mycc + cc)
+                    "(requires >=%d.%d)" % (cc + supported_cc)
                 )
                 raise CCSupportError(msg)
             else:
@@ -171,13 +192,13 @@ def find_closest_arch(mycc):
     return supported_ccs[-1]  # Choose the highest
 
 
-def get_arch_option(major, minor):
+def get_arch_option(major, minor, arch=""):
     """Matches with the closest architecture option"""
     if config.FORCE_CUDA_CC:
-        arch = config.FORCE_CUDA_CC
+        major, minor = config.FORCE_CUDA_CC
     else:
-        arch = find_closest_arch((major, minor))
-    return "compute_%d%d" % arch
+        major, minor = find_closest_arch((major, minor))
+    return f"compute_{major}{minor}{arch}"
 
 
 def get_lowest_supported_cc():

From 65bfd01af29e5b8a4ba4c401f0c03984ac1c986e Mon Sep 17 00:00:00 2001
From: Yevhenii Havrylko <yhavrylko@nvidia.com>
Date: Fri, 24 Oct 2025 12:13:50 -0700
Subject: [PATCH 02/10] Fix cc for pre (9, 0)

---
 numba_cuda/numba/cuda/codegen.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/numba_cuda/numba/cuda/codegen.py b/numba_cuda/numba/cuda/codegen.py
index 7f5560779..a4105fde0 100644
--- a/numba_cuda/numba/cuda/codegen.py
+++ b/numba_cuda/numba/cuda/codegen.py
@@ -204,8 +204,7 @@ def _ensure_cc(self, cc):
 
         device = devices.get_context().device
         cc = device.compute_capability
-        if cc >= (9, 0):
-            cc = (cc[0], cc[1], "a")
+        cc = (cc[0], cc[1], "a" if cc >= (9, 0) else "")
         return cc
 
     def get_asm_str(self, cc=None):

From 8e2c34bf3c45897b9e0fbc3da1ff87886caf5039 Mon Sep 17 00:00:00 2001
From: Yevhenii Havrylko <yhavrylko@nvidia.com>
Date: Thu, 8 Jan 2026 08:56:13 -0800
Subject: [PATCH 03/10] Add tests

---
 numba_cuda/numba/cuda/testing.py              |  4 ++
 .../cuda/tests/cudadrv/test_cuda_driver.py    | 47 ++++++++++++++++++-
 2 files changed, 50 insertions(+), 1 deletion(-)

diff --git a/numba_cuda/numba/cuda/testing.py b/numba_cuda/numba/cuda/testing.py
index 56469b349..0858be48a 100644
--- a/numba_cuda/numba/cuda/testing.py
+++ b/numba_cuda/numba/cuda/testing.py
@@ -300,6 +300,10 @@ def skip_unless_cc_75(fn):
     return unittest.skipUnless(cc_X_or_above(7, 5), "requires cc >= 7.5")(fn)
 
 
+def skip_unless_cc_90(fn):
+    return unittest.skipUnless(cc_X_or_above(9, 0), "requires cc >= 9.0")(fn)
+
+
 def xfail_unless_cudasim(fn):
     if config.ENABLE_CUDASIM:
         return fn
diff --git a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
index c12bf86e3..34a2e9ebe 100644
--- a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
+++ b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
@@ -2,6 +2,8 @@
 # SPDX-License-Identifier: BSD-2-Clause
 
 from ctypes import c_int, sizeof
+import cffi
+import numpy as np
 
 from numba.cuda.cudadrv.driver import host_to_device, device_to_host, driver
 from numba.cuda._compat import (
@@ -13,10 +15,12 @@
 
 from numba import cuda
 from numba.cuda.cudadrv import devices
-from numba.cuda.testing import unittest, CUDATestCase
+from numba.cuda.testing import unittest, CUDATestCase, skip_unless_cc_90
 from numba.cuda.testing import skip_on_cudasim
+from numba.core import types
 import contextlib
 
+
 ptx1 = """
     .version 1.4
     .target sm_10, map_f64_to_f32
@@ -390,5 +394,46 @@ def test_device_get_uuid(self):
         self.assertRegex(dev.uuid, uuid_format)
 
 
+@skip_unless_cc_90
+@skip_on_cudasim("CUDA asm unsupported in the simulator")
+class TestAcceleratedArchitecture(CUDATestCase):
+    def test_device_arch_specific(self):
+        set_desc = cuda.CUSource("""
+        #include <cuda_fp16.h>
+
+        extern "C" __device__
+        int set_descriptor(int *out, int* smem) {
+            unsigned usmem = __cvta_generic_to_shared(smem);
+            asm volatile("tensormap.replace.tile.rank.shared::cta.b1024.b32 [%0], 2;" :: "r"(usmem));
+            return 0;
+        }
+        """)
+
+        set_descriptor = cuda.declare_device(
+            "set_descriptor",
+            types.int32(types.CPointer(types.int32)),
+            link=[set_desc],
+        )
+
+        ffi = cffi.FFI()
+
+        @cuda.jit
+        def kernel(a):
+            sm = cuda.shared.array(1, dtype=np.int32)
+            data_ptr = ffi.from_buffer(sm)
+            set_descriptor(data_ptr)
+
+            # just to prevent optimization:
+            sm[0] = 2
+            cuda.syncthreads()
+            a[0] = sm[0]
+
+        a = np.ones(1, dtype=np.int32)
+
+        kernel[1, 1](a)
+
+        assert a[0] == 2
+
+
 if __name__ == "__main__":
     unittest.main()

From 06478526bee90f5ef4ebd144867f89fb7bb99ed7 Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Thu, 8 Jan 2026 20:07:07 +0000
Subject: [PATCH 04/10] Accept compute capabilities with no family

---
 numba_cuda/numba/cuda/cudadrv/driver.py | 6 +++++-
 numba_cuda/numba/cuda/cudadrv/nvrtc.py  | 2 ++
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/numba_cuda/numba/cuda/cudadrv/driver.py b/numba_cuda/numba/cuda/cudadrv/driver.py
index ec5580bf1..40a12ee9a 100644
--- a/numba_cuda/numba/cuda/cudadrv/driver.py
+++ b/numba_cuda/numba/cuda/cudadrv/driver.py
@@ -2303,7 +2303,11 @@ def __init__(
         lto=None,
         additional_flags=None,
     ):
-        arch = f"sm_{cc[0]}{cc[1]}{cc[2]}"
+        if len(cc) == 3:
+            arch = f"sm_{cc[0]}{cc[1]}{cc[2]}"
+        else:
+            arch = f"sm_{cc[0]}{cc[1]}"
+
         self.max_registers = max_registers if max_registers else None
         self.lineinfo = lineinfo
         self.cc = cc
diff --git a/numba_cuda/numba/cuda/cudadrv/nvrtc.py b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
index ca4bd16fd..069bc0865 100644
--- a/numba_cuda/numba/cuda/cudadrv/nvrtc.py
+++ b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
@@ -36,6 +36,8 @@ def _verify_cc_tuple(cc):
 
     if len(cc) == 3:
         cc, arch = (cc[0], cc[1]), cc[2]
+    else:
+        arch = ""
 
     if arch not in ("", "a", "f"):
         raise ValueError(

From a0d7b7b0d4ece10e8e835202dd3ff35ec0548ec9 Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Thu, 8 Jan 2026 20:36:21 +0000
Subject: [PATCH 05/10] Update pixi.lock

---
 pixi.lock | 30 +++++++++++++++---------------
 1 file changed, 15 insertions(+), 15 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index b6bf0e4e8..94de965ec 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -18054,7 +18054,7 @@ packages:
   - numpy >=1.21,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18078,7 +18078,7 @@ packages:
   - numpy >=1.21,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18102,7 +18102,7 @@ packages:
   - numpy >=1.21,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18126,7 +18126,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18150,7 +18150,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18174,7 +18174,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18198,7 +18198,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18222,7 +18222,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18246,7 +18246,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18270,7 +18270,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18294,7 +18294,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18318,7 +18318,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18342,7 +18342,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18366,7 +18366,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - conda: .
@@ -18390,7 +18390,7 @@ packages:
   - numpy >=1.23,<3
   license: BSD-2-Clause
   input:
-    hash: 2a1b1407e123167bcf4af0d488c2c2ad1bd42711c50bef7a9b2990890a9542d7
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
     globs:
     - pyproject.toml
 - pypi: https://files.pythonhosted.org/packages/5e/a6/9ca0eecc489640615642a6cbc0ca9e10df70df38c4d43f5a928ff18d8827/numpy-2.3.5-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl

From 29e04eab9fe2eb31fad8ce92066dc2b727772a10 Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Mon, 12 Jan 2026 11:44:19 +0000
Subject: [PATCH 06/10] Ensure get_arch_option handles arch correctly

When `config.FORCE_CUDA_CC` is set, the arch option from it should be
used regardless of what is passed into `get_arch_option()`.

Also, if the discovered CC is not an exact match for the requested one,
it is not valid to use arch-specific versions because the arch-specific
PTX will not be compatible with the device being targeted.
---
 numba_cuda/numba/cuda/cudadrv/nvrtc.py        | 20 +++++++++++++++--
 .../cuda/tests/cudadrv/test_cuda_driver.py    | 22 +++++++++++++++++--
 2 files changed, 38 insertions(+), 4 deletions(-)

diff --git a/numba_cuda/numba/cuda/cudadrv/nvrtc.py b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
index 069bc0865..e14d1b6c9 100644
--- a/numba_cuda/numba/cuda/cudadrv/nvrtc.py
+++ b/numba_cuda/numba/cuda/cudadrv/nvrtc.py
@@ -213,9 +213,25 @@ def find_closest_arch(cc):
 def get_arch_option(major, minor, arch=""):
     """Matches with the closest architecture option"""
     if config.FORCE_CUDA_CC:
-        major, minor = config.FORCE_CUDA_CC
+        fcc = config.FORCE_CUDA_CC
+        major, minor = fcc[0], fcc[1]
+        if len(fcc) == 3:
+            arch = fcc[2]
+        else:
+            arch = ""
     else:
-        major, minor = find_closest_arch((major, minor))
+        new_major, new_minor = find_closest_arch((major, minor))
+        if (new_major, new_minor) != (major, minor):
+            # If we picked a different major / minor, then using an
+            # arch-specific version is invalid
+            if arch != "":
+                raise ValueError(
+                    f"Can't use arch-specific compute_{major}{minor}{arch} with "
+                    "closest found compute capability "
+                    f"compute_{new_major}{new_minor}"
+                )
+        major, minor = new_major, new_minor
+
     return f"compute_{major}{minor}{arch}"
 
 
diff --git a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
index 34a2e9ebe..5774784fd 100644
--- a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
+++ b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_driver.py
@@ -14,9 +14,10 @@
 )
 
 from numba import cuda
-from numba.cuda.cudadrv import devices
+from numba.cuda.cudadrv import devices, nvrtc
 from numba.cuda.testing import unittest, CUDATestCase, skip_unless_cc_90
 from numba.cuda.testing import skip_on_cudasim
+from numba.cuda.tests.support import override_config
 from numba.core import types
 import contextlib
 
@@ -394,9 +395,9 @@ def test_device_get_uuid(self):
         self.assertRegex(dev.uuid, uuid_format)
 
 
-@skip_unless_cc_90
 @skip_on_cudasim("CUDA asm unsupported in the simulator")
 class TestAcceleratedArchitecture(CUDATestCase):
+    @skip_unless_cc_90
     def test_device_arch_specific(self):
         set_desc = cuda.CUSource("""
         #include <cuda_fp16.h>
@@ -434,6 +435,23 @@ def kernel(a):
 
         assert a[0] == 2
 
+    def test_get_arch_option_force_cc(self):
+        with override_config("FORCE_CUDA_CC", (8, 0)):
+            arch = nvrtc.get_arch_option(9, 0, "a")
+            self.assertEqual("compute_80", arch)
+
+    def test_get_arch_option_force_cc_arch_specific(self):
+        with override_config("FORCE_CUDA_CC", (9, 0, "a")):
+            arch = nvrtc.get_arch_option(9, 0)
+            self.assertEqual("compute_90a", arch)
+
+    def test_get_arch_option_illegal_arch_specific(self):
+        # Using a fictitious very high compute capability (major 99) for this
+        # test to ensure future toolkits are unlikely to provide an exact match
+        msg = "Can't use arch-specific compute_990a with"
+        with self.assertRaisesRegex(ValueError, msg):
+            nvrtc.get_arch_option(99, 0, "a")
+
 
 if __name__ == "__main__":
     unittest.main()

From 02b815a4d346749d26f0cbb83751112a436da9b1 Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Mon, 12 Jan 2026 12:02:56 +0000
Subject: [PATCH 07/10] Test arch-specific CCs with `compile_ptx()`

---
 numba_cuda/numba/cuda/tests/cudapy/test_compiler.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py b/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
index ae668157d..935ba55fa 100644
--- a/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
+++ b/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
@@ -661,6 +661,13 @@ def use_nanosleep(x):
             ),
         )
 
+    def test_compile_ptx_arch_specific(self):
+        ptx, resty = cuda.compile_ptx(lambda: None, tuple(), cc=(9, 0, "a"))
+        self.assertIn(".target sm_90a", ptx)
+
+        ptx, resty = cuda.compile_ptx(lambda: None, tuple(), cc=(10, 0, "f"))
+        self.assertIn(".target sm_100f", ptx)
+
 
 @skip_on_cudasim("Compilation unsupported in the simulator")
 class TestCompileWithLaunchBounds(unittest.TestCase):

From 6fe89f93405e8d710b6004d82fc9ef83c297a30e Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Mon, 12 Jan 2026 12:04:02 +0000
Subject: [PATCH 08/10] Use pixi.lock from main

---
 pixi.lock | 5875 +++++++++++++++++++++++------------------------------
 1 file changed, 2544 insertions(+), 3331 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index 94de965ec..285794d81 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -12,166 +12,169 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.11.12-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.1.4-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cffi-2.0.0-py314h6fefde3_1.conda
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       - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
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-      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.20.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.20.2-pyhd8ed1ab_0.conda
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-  - sysroot_linux-aarch64
-  - tzdata
-  license: GPL-3.0-only WITH GCC-exception-3.1
-  purls: []
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-15.2.0-h03e2352_15.conda
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-  md5: 85b6576cfb40717bc76235e879617224
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-14.3.0-h0d4f5d4_16.conda
+  sha256: 060c16a21fa60ba7ff632a7dfa56167a5b8e833b199b270ffc8831313370aa49
+  md5: c31908937ef3f628f64728135b7fa6b3
   depends:
-  - gcc_impl_linux-aarch64 15.2.0 h50d3cce_15
-  - libstdcxx-devel_linux-aarch64 15.2.0 ha7b1723_115
+  - gcc_impl_linux-aarch64 14.3.0 hda29b82_16
+  - libstdcxx-devel_linux-aarch64 14.3.0 h57c8d61_116
   - sysroot_linux-aarch64
   - tzdata
   license: GPL-3.0-only WITH GCC-exception-3.1
+  license_family: GPL
   purls: []
-  size: 14630217
-  timestamp: 1764836536386
+  size: 13534642
+  timestamp: 1765256828434
 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-15.2.0-h03e2352_16.conda
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   md5: f1f0e9c2459ee137fd2d0280f08d7e93
@@ -12785,43 +12742,32 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-he6f32d1_14.conda
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-  md5: 9c792be16fc0c2b5ed6d1f3b768876e8
+- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-h310e576_17.conda
+  sha256: 90ccb0df50254feb5b4e539b06e3d2c3baf5c37e40579224a277ab164566a6a0
+  md5: 94474857477981fedf74cf7c47c88ba5
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   - gxx_impl_linux-64 14.3.0.*
-  - gcc_linux-64 ==14.3.0 h298d278_14
-  - binutils_linux-64
-  - sysroot_linux-64
-  license: BSD-3-Clause
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-  size: 27404
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-h40a1807_16.conda
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-  depends:
-  - gxx_impl_linux-64 15.2.0.*
-  - gcc_linux-64 ==15.2.0 h862fb80_16
+  - gcc_linux-64 ==14.3.0 h298d278_17
   - binutils_linux-64
   - sysroot_linux-64
   license: BSD-3-Clause
   license_family: BSD
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-hd02bce6_14.conda
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-  md5: a8f19bdd3319ec563ed320178f1f750a
+  size: 27464
+  timestamp: 1766347929379
+- conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-h2d7d49d_17.conda
+  sha256: 5881af6f095470532d04a1b0a34f7dfbd3e337bb93ba8441c669860c4431e136
+  md5: 84575f6344201cb102e4c66028d1ed86
   depends:
   - gxx_impl_linux-64 15.2.0.*
-  - gcc_linux-64 ==15.2.0 h862fb80_14
+  - gcc_linux-64 ==15.2.0 h862fb80_17
   - binutils_linux-64
   - sysroot_linux-64
   license: BSD-3-Clause
+  license_family: BSD
   purls: []
-  size: 27397
-  timestamp: 1764713654836
+  size: 27461
+  timestamp: 1766348017163
 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-12.4.0-h3f57e68_10.conda
   sha256: 19edef472580cef8c145ccb307dd71ed2b7c18ac86e43aafce356047ce0f8352
   md5: ba65e3da87da43ba05bed772c89d084d
@@ -12835,43 +12781,32 @@ packages:
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   size: 30955
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-14.3.0-hef95cfa_14.conda
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-  md5: ba095fd345f927689347487a8020a598
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-14.3.0-h7476c01_17.conda
+  sha256: d8934358913c36e58273b09e3e81d74b78e7dfb41157717ce7b9fbb1bf6da538
+  md5: 8b396fba15df31abf963a948e3e5af50
   depends:
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-  - gcc_linux-aarch64 ==14.3.0 h118592a_14
-  - binutils_linux-aarch64
-  - sysroot_linux-aarch64
-  license: BSD-3-Clause
-  purls: []
-  size: 27162
-  timestamp: 1764713836536
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-h2d1e4cd_16.conda
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-  depends:
-  - gxx_impl_linux-aarch64 15.2.0.*
-  - gcc_linux-aarch64 ==15.2.0 h0139441_16
+  - gcc_linux-aarch64 ==14.3.0 h118592a_17
   - binutils_linux-aarch64
   - sysroot_linux-aarch64
   license: BSD-3-Clause
   license_family: BSD
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   size: 27209
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-h92f20a2_14.conda
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-  md5: 1660386135fadcbc3c2587ac028c8983
+  timestamp: 1766347983467
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-ha9de7cb_17.conda
+  sha256: 5daa4f13900f6caf91e2d3ed390f3df4c505067d8ea9bfebf6dcb4b774132559
+  md5: ad4cf12c620439460f8cbac418c9f96b
   depends:
   - gxx_impl_linux-aarch64 15.2.0.*
-  - gcc_linux-aarch64 ==15.2.0 h0139441_14
+  - gcc_linux-aarch64 ==15.2.0 h0139441_17
   - binutils_linux-aarch64
   - sysroot_linux-aarch64
   license: BSD-3-Clause
+  license_family: BSD
   purls: []
-  size: 27167
-  timestamp: 1764713573220
+  size: 27213
+  timestamp: 1766348002575
 - conda: https://conda.anaconda.org/conda-forge/noarch/h2-4.3.0-pyhcf101f3_0.conda
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   md5: 164fc43f0b53b6e3a7bc7dce5e4f1dc9
@@ -12883,7 +12818,7 @@ packages:
   license: MIT
   license_family: MIT
   purls:
-  - pkg:pypi/h2?source=compressed-mapping
+  - pkg:pypi/h2?source=hash-mapping
   size: 95967
   timestamp: 1756364871835
 - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
@@ -12908,6 +12843,41 @@ packages:
   - pkg:pypi/hyperframe?source=hash-mapping
   size: 17397
   timestamp: 1737618427549
+- conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.1-h33c6efd_0.conda
+  sha256: 7d6463d0be5092b2ae8f2fad34dc84de83eab8bd44cc0d4be8931881c973c48f
+  md5: 518e9bbbc3e3486d6a4519192ba690f8
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=14
+  - libstdcxx >=14
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 12722920
+  timestamp: 1766299101259
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.1-hb1525cb_0.conda
+  sha256: 550c581d08eefe420f9ed14148f1c1d59a3e33de78806a1b8d610d207d06374c
+  md5: 5eba836ceb0cccf969d9518ca884de2a
+  depends:
+  - libgcc >=14
+  - libstdcxx >=14
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 12835377
+  timestamp: 1766304007889
+- conda: https://conda.anaconda.org/conda-forge/win-64/icu-78.1-h637d24d_0.conda
+  sha256: bee083d5a0f05c380fcec1f30a71ef5518b23563aeb0a21f6b60b792645f9689
+  md5: cb8048bed35ef01431184d6a88e46b3e
+  depends:
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 13849749
+  timestamp: 1766299627069
 - conda: https://conda.anaconda.org/conda-forge/noarch/identify-1.2.2-py_0.tar.bz2
   sha256: 8b7a313fb8a50936b32054a01dd044874616e35b4e239bb7d2a42e30e7ab0a5d
   md5: 4b64d3379406ae93336bbc6ea9f5128a
@@ -12977,16 +12947,6 @@ packages:
   - pkg:pypi/jinja2?source=compressed-mapping
   size: 120685
   timestamp: 1764517220861
-- conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_8.conda
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-  md5: ff007ab0f0fdc53d245972bba8a6d40c
-  constrains:
-  - sysroot_linux-64 ==2.28
-  license: LGPL-2.0-or-later AND LGPL-2.0-or-later WITH exceptions AND GPL-2.0-or-later
-  license_family: GPL
-  purls: []
-  size: 1272697
-  timestamp: 1752669126073
 - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_9.conda
   sha256: 41557eeadf641de6aeae49486cef30d02a6912d8da98585d687894afd65b356a
   md5: 86d9cba083cd041bfbf242a01a7a1999
@@ -12997,16 +12957,6 @@ packages:
   purls: []
   size: 1278712
   timestamp: 1765578681495
-- conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-aarch64-4.18.0-h05a177a_8.conda
-  sha256: 9d0a86bd0c52c39db8821405f6057bc984789d36e15e70fa5c697f8ba83c1a19
-  md5: 2ab884dda7f1a08758fe12c32cc31d08
-  constrains:
-  - sysroot_linux-aarch64 ==2.28
-  license: LGPL-2.0-or-later AND LGPL-2.0-or-later WITH exceptions AND GPL-2.0-or-later
-  license_family: GPL
-  purls: []
-  size: 1244709
-  timestamp: 1752669116535
 - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-aarch64-4.18.0-h05a177a_9.conda
   sha256: 5d224bf4df9bac24e69de41897c53756108c5271a0e5d2d2f66fd4e2fbc1d84b
   md5: bb3b7cad9005f2cbf9d169fb30263f3e
@@ -13030,9 +12980,9 @@ packages:
   purls: []
   size: 46768
   timestamp: 1732916943523
-- conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-default_hbd61a6d_104.conda
-  sha256: 9e191baf2426a19507f1d0a17be0fdb7aa155cdf0f61d5a09c808e0a69464312
-  md5: a6abd2796fc332536735f68ba23f7901
+- conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-default_hbd61a6d_105.conda
+  sha256: 1027bd8aa0d5144e954e426ab6218fd5c14e54a98f571985675468b339c808ca
+  md5: 3ec0aa5037d39b06554109a01e6fb0c6
   depends:
   - __glibc >=2.17,<3.0.a0
   - zstd >=1.5.7,<1.6.0a0
@@ -13041,11 +12991,11 @@ packages:
   license: GPL-3.0-only
   license_family: GPL
   purls: []
-  size: 725545
-  timestamp: 1764007826689
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.45-default_h1979696_104.conda
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-  md5: 28035705fe0c977ea33963489cd008ad
+  size: 730831
+  timestamp: 1766513089214
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.45-default_h1979696_105.conda
+  sha256: 12e7341b89e9ea319a3b4de03d02cd988fa02b8a678f4e46779515009b5e475c
+  md5: 849c4cbbf8dd1d71e66c13afed1d2f12
   depends:
   - zstd >=1.5.7,<1.6.0a0
   constrains:
@@ -13053,8 +13003,8 @@ packages:
   license: GPL-3.0-only
   license_family: GPL
   purls: []
-  size: 875534
-  timestamp: 1764007911054
+  size: 876257
+  timestamp: 1766513180236
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20250512.1-cxx17_hba17884_0.conda
   sha256: dcd1429a1782864c452057a6c5bc1860f2b637dc20a2b7e6eacd57395bbceff8
   md5: 83b160d4da3e1e847bf044997621ed63
@@ -13099,41 +13049,6 @@ packages:
   purls: []
   size: 1615210
   timestamp: 1750194549591
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-4_h4a7cf45_openblas.conda
-  build_number: 4
-  sha256: f35fee1eb3fe1a80b2c8473f145a830cf6f98c3b15b232b256b93d44bd9c93b3
-  md5: 14ff9fdfbd8bd590fca383b995470711
-  depends:
-  - libopenblas >=0.3.30,<0.3.31.0a0
-  - libopenblas >=0.3.30,<1.0a0
-  constrains:
-  - liblapack  3.11.0   4*_openblas
-  - blas 2.304   openblas
-  - mkl <2026
-  - libcblas   3.11.0   4*_openblas
-  - liblapacke 3.11.0   4*_openblas
-  license: BSD-3-Clause
-  purls: []
-  size: 18529
-  timestamp: 1764823833499
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-4_h5875eb1_mkl.conda
-  build_number: 4
-  sha256: 4f7754845719e52b3440b4d7c14d21ae435aefa393aaf4186f1de8bb79103d1b
-  md5: bd1a86e560c3b26961279ef6b6e8d45f
-  depends:
-  - mkl >=2025.3.0,<2026.0a0
-  constrains:
-  - blas 2.304   mkl
-  - liblapacke 3.11.0   4*_mkl
-  - liblapack  3.11.0   4*_mkl
-  - libcblas   3.11.0   4*_mkl
-  track_features:
-  - blas_mkl
-  - blas_mkl_2
-  license: BSD-3-Clause
-  purls: []
-  size: 18887
-  timestamp: 1764823790196
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-5_h4a7cf45_openblas.conda
   build_number: 5
   sha256: 18c72545080b86739352482ba14ba2c4815e19e26a7417ca21a95b76ec8da24c
@@ -13152,23 +13067,25 @@ packages:
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   size: 18213
   timestamp: 1765818813880
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libblas-3.11.0-4_haddc8a3_openblas.conda
-  build_number: 4
-  sha256: 6da3f5e1506f2b98fb741ab4ed705b7914a691f4f44ca18e28c3543b10185021
-  md5: 10471558ac2b0c1b4dcd5e620fd65bfe
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-5_h5875eb1_mkl.conda
+  build_number: 5
+  sha256: 328d64d4eb51047c39a8039a30eb47695855829d0a11b72d932171cb1dcdfad3
+  md5: 9d2f2e3a943d38f972ceef9cde8ba4bf
   depends:
-  - libopenblas >=0.3.30,<0.3.31.0a0
-  - libopenblas >=0.3.30,<1.0a0
+  - mkl >=2025.3.0,<2026.0a0
   constrains:
-  - mkl <2026
-  - liblapack  3.11.0   4*_openblas
-  - blas 2.304   openblas
-  - libcblas   3.11.0   4*_openblas
-  - liblapacke 3.11.0   4*_openblas
+  - liblapack  3.11.0   5*_mkl
+  - liblapacke 3.11.0   5*_mkl
+  - libcblas   3.11.0   5*_mkl
+  - blas 2.305   mkl
+  track_features:
+  - blas_mkl
+  - blas_mkl_2
   license: BSD-3-Clause
+  license_family: BSD
   purls: []
-  size: 18577
-  timestamp: 1764823752463
+  size: 18744
+  timestamp: 1765818556597
 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libblas-3.11.0-5_haddc8a3_openblas.conda
   build_number: 5
   sha256: 700f3c03d0fba8e687a345404a45fbabe781c1cf92242382f62cef2948745ec4
@@ -13187,21 +13104,6 @@ packages:
   purls: []
   size: 18369
   timestamp: 1765818610617
-- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.11.0-4_hf2e6a31_mkl.conda
-  build_number: 4
-  sha256: 0c6ecdabcd3c5b92c7be68a65c30c29983040dd81f502d2e9ad3763fdbbabdef
-  md5: 97ec87aab53fb310e6c19cde2eec1de2
-  depends:
-  - mkl >=2025.3.0,<2026.0a0
-  constrains:
-  - liblapacke 3.11.0   4*_mkl
-  - libcblas   3.11.0   4*_mkl
-  - liblapack  3.11.0   4*_mkl
-  - blas 2.304   mkl
-  license: BSD-3-Clause
-  purls: []
-  size: 67784
-  timestamp: 1764824188313
 - conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.11.0-5_hf2e6a31_mkl.conda
   build_number: 5
   sha256: f0cb7b2697461a306341f7ff32d5b361bb84f3e94478464c1e27ee01fc8f276b
@@ -13241,36 +13143,6 @@ packages:
   purls: []
   size: 108542
   timestamp: 1762350753349
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-4_h0358290_openblas.conda
-  build_number: 4
-  sha256: 7abc88e2fdccddab27d2a889b9c9063df84a05766cc24828c9b5ca879f25c92c
-  md5: 25f5e5af61cee1ffedd9b4c9947d3af8
-  depends:
-  - libblas 3.11.0 4_h4a7cf45_openblas
-  constrains:
-  - liblapack  3.11.0   4*_openblas
-  - blas 2.304   openblas
-  - liblapacke 3.11.0   4*_openblas
-  license: BSD-3-Clause
-  purls: []
-  size: 18521
-  timestamp: 1764823852735
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From 3e8440a203f414b96e17c45ee4a88da38dbf2629 Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Mon, 12 Jan 2026 12:17:26 +0000
Subject: [PATCH 09/10] Delete and recreate pixi.lock

---
 pixi.lock | 830 +++++++++++++++++++++++++++++-------------------------
 1 file changed, 442 insertions(+), 388 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index 285794d81..51fd489c6 100644
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@@ -5804,7 +5804,7 @@ packages:
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   license_family: MIT
   purls:
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+  - pkg:pypi/cfgv?source=hash-mapping
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   license: MIT and PSF-2.0
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+  - pkg:pypi/exceptiongroup?source=hash-mapping
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-  md5: 7e7cf4d6c2be6991e6ae2b3f4331701c
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+  - pkg:pypi/filelock?source=hash-mapping
+  size: 18661
+  timestamp: 1768022315929
+- conda: https://conda.anaconda.org/conda-forge/linux-64/fmt-12.1.0-hff5e90c_0.conda
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-  timestamp: 1760369692240
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   - python_abi 3.14.* *_cp314
   - numpy >=1.23,<3
   license: BSD-2-Clause
+  input:
+    hash: fbf2aec967fc793f2faac9564bd83b483897225058f2e503c8dd8f00d416eda9
+    globs:
+    - pyproject.toml
 - conda: .
   name: numba-cuda
   version: 0.23.0
@@ -17898,20 +17950,24 @@ packages:
   - python_abi 3.14.* *_cp314
   - numpy >=1.23,<3
   license: BSD-2-Clause
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+  input:
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+    globs:
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   name: numpy
-  version: 2.4.0
-  sha256: 3d857f55e7fdf7c38ab96c4558c95b97d1c685be6b05c249f5fdafcbd6f9899e
+  version: 2.4.1
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   name: numpy
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-  version: 2.4.0
-  sha256: d9e6a7664ddd9746e20b7325351fe1a8408d0a2bf9c63b5e898290ddc8f09544
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/pytorch-2.9.1-cuda129_mkl_py312_h04de0ce_301.conda
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-  md5: 4879ab4fdb998a30ac87124e4a7e1471
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+  md5: 062a64a99d83ebf707bc5ee5fa32ff50
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   - __glibc >=2.17,<3.0.a0
@@ -19350,7 +19406,7 @@ packages:
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   - cudnn >=9.10.2.21,<10.0a0
   - filelock
-  - fmt >=12.0.0,<12.1.0a0
+  - fmt >=12.1.0,<12.2.0a0
   - fsspec
   - jinja2
   - libabseil * cxx17*
@@ -19368,12 +19424,12 @@ packages:
   - libmagma >=2.9.0,<2.9.1.0a0
   - libprotobuf >=6.31.1,<6.31.2.0a0
   - libstdcxx >=14
-  - libtorch 2.9.1 cuda129_mkl_hce6efb5_301
+  - libtorch 2.9.1 cuda129_mkl_hf5f578d_302
   - libuv >=1.51.0,<2.0a0
   - libzlib >=1.3.1,<2.0a0
-  - llvm-openmp >=21.1.7
+  - llvm-openmp >=21.1.8
   - mkl >=2025.3.0,<2026.0a0
-  - nccl >=2.28.9.1,<3.0a0
+  - nccl >=2.29.2.1,<3.0a0
   - networkx
   - numpy >=1.23,<3
   - optree >=0.13.0
@@ -19387,17 +19443,17 @@ packages:
   - triton 3.5.1
   - typing_extensions >=4.10.0
   constrains:
-  - pytorch-cpu <0.0a0
   - pytorch-gpu 2.9.1
+  - pytorch-cpu <0.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls:
   - pkg:pypi/torch?source=hash-mapping
-  size: 25697443
-  timestamp: 1764979992711
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/pytorch-2.9.1-cuda129_generic_py312_hd4d6f83_201.conda
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-  md5: 588a05ea682d674d298a6666e7cd77dc
+  size: 25623208
+  timestamp: 1768009260862
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/pytorch-2.9.1-cuda129_generic_py312_h1c6fe66_202.conda
+  sha256: 3f996db0d72ea8e19c870882209975af6533cf91e1df54983ff1839c00b7825e
+  md5: b64e4f5cc18baab6308905e0ef120c48
   depends:
   - __cuda
   - _openmp_mutex * *_llvm
@@ -19410,7 +19466,7 @@ packages:
   - cuda-version >=12.9,<13
   - cudnn >=9.10.2.21,<10.0a0
   - filelock
-  - fmt >=12.0.0,<12.1.0a0
+  - fmt >=12.1.0,<12.2.0a0
   - fsspec
   - jinja2
   - libabseil * cxx17*
@@ -19428,11 +19484,11 @@ packages:
   - libmagma >=2.9.0,<2.9.1.0a0
   - libprotobuf >=6.31.1,<6.31.2.0a0
   - libstdcxx >=13
-  - libtorch 2.9.1 cuda129_generic_hd20f0ec_201
+  - libtorch 2.9.1 cuda129_generic_hc774871_202
   - libuv >=1.51.0,<2.0a0
   - libzlib >=1.3.1,<2.0a0
-  - llvm-openmp >=21.1.6
-  - nccl >=2.28.9.1,<3.0a0
+  - llvm-openmp >=21.1.8
+  - nccl >=2.29.2.1,<3.0a0
   - networkx
   - nomkl
   - numpy >=1.23,<3
@@ -19454,11 +19510,11 @@ packages:
   license_family: BSD
   purls:
   - pkg:pypi/torch?source=hash-mapping
-  size: 25181165
-  timestamp: 1764760870201
-- conda: https://conda.anaconda.org/conda-forge/win-64/pytorch-2.9.1-cuda128_mkl_py312_h003053b_300.conda
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-  md5: b87082d25e9d4ec44f02503fb7acc40f
+  size: 25252154
+  timestamp: 1768061904538
+- conda: https://conda.anaconda.org/conda-forge/win-64/pytorch-2.9.1-cuda128_mkl_py312_h5b42cb5_302.conda
+  sha256: a6c67614db81cfa144de92b1987808d793ff74d00480d6ec1791e0491db9b559
+  md5: 7a00fe575054e63eda01ebdfa875ca6e
   depends:
   - __cuda
   - cuda-cudart >=12.8.90,<13.0a0
@@ -19467,7 +19523,7 @@ packages:
   - cuda-version >=12.8,<13
   - cudnn >=9.10.2.21,<10.0a0
   - filelock
-  - fmt >=12.0.0,<12.1.0a0
+  - fmt >=12.1.0,<12.2.0a0
   - fsspec
   - jinja2
   - libabseil * cxx17*
@@ -19482,10 +19538,10 @@ packages:
   - libcusparse >=12.5.8.93,<13.0a0
   - libmagma >=2.9.0,<2.9.1.0a0
   - libprotobuf >=6.31.1,<6.31.2.0a0
-  - libtorch 2.9.1 cuda128_mkl_hbf96477_300
+  - libtorch 2.9.1 cuda128_mkl_h5af97b6_302
   - libuv >=1.51.0,<2.0a0
   - libzlib >=1.3.1,<2.0a0
-  - llvm-openmp >=21.1.6
+  - llvm-openmp >=21.1.8
   - mkl >=2025.3.0,<2026.0a0
   - networkx
   - numpy >=1.23,<3
@@ -19502,44 +19558,44 @@ packages:
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   constrains:
-  - pytorch-cpu <0.0a0
   - pytorch-gpu 2.9.1
+  - pytorch-cpu <0.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls:
   - pkg:pypi/torch?source=hash-mapping
-  size: 23426888
-  timestamp: 1764060218065
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pytorch-gpu-2.9.1-cuda129_mkl_h0d04637_301.conda
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-  md5: 9cc563c8a35e1629264bc537df8ecfdd
+  size: 23516399
+  timestamp: 1767993503010
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pytorch-gpu-2.9.1-cuda129_mkl_h0d04637_302.conda
+  sha256: 9eec128aa982249b6c8c991563a55f28af1ab17584a65713b3e58cd9bc8b03f2
+  md5: 25ce8495e95d3aaf779e8f224ecd823c
   depends:
-  - pytorch 2.9.1 cuda*_mkl*301
+  - pytorch 2.9.1 cuda*_mkl*302
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 50240
-  timestamp: 1764982604740
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/pytorch-gpu-2.9.1-cuda129_generic_hdc58e1e_201.conda
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-  md5: 54cd1aa1098a94105bc39119baffed71
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+  timestamp: 1768009337031
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/pytorch-gpu-2.9.1-cuda129_generic_hdc58e1e_202.conda
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+  md5: 958fc5a20f0ba8f4c41ff5f3e7f5927d
   depends:
-  - pytorch 2.9.1 cuda*_generic*201
+  - pytorch 2.9.1 cuda*_generic*202
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 50294
-  timestamp: 1764763502406
-- conda: https://conda.anaconda.org/conda-forge/win-64/pytorch-gpu-2.9.1-cuda128_mkl_hc88b545_300.conda
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-  md5: 5e5d33170ccadec46b57d0ef0eea7c39
+  size: 50284
+  timestamp: 1768064600446
+- conda: https://conda.anaconda.org/conda-forge/win-64/pytorch-gpu-2.9.1-cuda128_mkl_hc88b545_302.conda
+  sha256: c09fd639ef70e00b585e7ab94603077cfa9159db214c9eacf6822796cdf17d13
+  md5: 05dfe53e41c1c1c3727a1de87981b00e
   depends:
-  - pytorch 2.9.1 cuda*_mkl*300
+  - pytorch 2.9.1 cuda*_mkl*302
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 51059
-  timestamp: 1764066709921
+  size: 50970
+  timestamp: 1768000171960
 - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2025.2-pyhd8ed1ab_0.conda
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@@ -20152,18 +20208,17 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
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-  md5: d2732eb636c264dc9aa4cbee404b1a53
+- conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.0-pyhcf101f3_0.conda
+  sha256: 62940c563de45790ba0f076b9f2085a842a65662268b02dd136a8e9b1eaf47a8
+  md5: 72e780e9aa2d0a3295f59b1874e3768b
   depends:
   - python >=3.10
   - python
   license: MIT
-  license_family: MIT
   purls:
   - pkg:pypi/tomli?source=compressed-mapping
-  size: 20973
-  timestamp: 1760014679845
+  size: 21453
+  timestamp: 1768146676791
 - conda: https://conda.anaconda.org/conda-forge/linux-64/triton-3.5.1-cuda129py312h811769c_0.conda
   sha256: a7c3b16ccc3ae6534fd4ffcac640a97da069653184346aaae93b2666e2b8b409
   md5: 3edceb734aaf38cef0cf862a542ea4a0
@@ -20549,9 +20604,9 @@ packages:
   purls: []
   size: 115235
   timestamp: 1767320173250
-- conda: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.36.0-pyhd8ed1ab_0.conda
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-  md5: c9a9b6e144b880308f5eedc905fe503d
+- conda: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.36.1-pyhd8ed1ab_0.conda
+  sha256: fa0a21fdcd0a8e6cf64cc8cd349ed6ceb373f09854fd3c4365f0bc4586dccf9a
+  md5: 6b0259cea8ffa6b66b35bae0ca01c447
   depends:
   - distlib >=0.3.7,<1
   - filelock >=3.20.1,<4
@@ -20559,11 +20614,10 @@ packages:
   - python >=3.10
   - typing_extensions >=4.13.2
   license: MIT
-  license_family: MIT
   purls:
   - pkg:pypi/virtualenv?source=hash-mapping
-  size: 4403353
-  timestamp: 1767880093070
+  size: 4404318
+  timestamp: 1768069793682
 - conda: https://conda.anaconda.org/conda-forge/win-64/vs2019_win-64-19.29.30139-h7dcff83_34.conda
   sha256: 80097a8ddc6511c6a4300b15d79f1c15d3111291229c65e45e5d8f96f6eafa3c
   md5: 0c9b55f300635a96b2661f8bb6a6d5a4

From f91c22e9ec95ceaacb46ce39fcacc147218c558d Mon Sep 17 00:00:00 2001
From: Graham Markall <gmarkall@nvidia.com>
Date: Mon, 12 Jan 2026 16:41:54 +0000
Subject: [PATCH 10/10] Only test with 100f arch when CTK >= 12.9

---
 numba_cuda/numba/cuda/tests/cudapy/test_compiler.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py b/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
index 935ba55fa..ee3691ca1 100644
--- a/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
+++ b/numba_cuda/numba/cuda/tests/cudapy/test_compiler.py
@@ -13,6 +13,7 @@
     compile_all,
     LinkableCode,
 )
+from numba.cuda.cudadrv import nvrtc
 from numba.cuda.testing import skip_on_cudasim, unittest, CUDATestCase
 
 TEST_BIN_DIR = os.getenv("NUMBA_CUDA_TEST_BIN_DIR")
@@ -665,8 +666,11 @@ def test_compile_ptx_arch_specific(self):
         ptx, resty = cuda.compile_ptx(lambda: None, tuple(), cc=(9, 0, "a"))
         self.assertIn(".target sm_90a", ptx)
 
-        ptx, resty = cuda.compile_ptx(lambda: None, tuple(), cc=(10, 0, "f"))
-        self.assertIn(".target sm_100f", ptx)
+        if nvrtc._get_nvrtc_version() >= (12, 9):
+            ptx, resty = cuda.compile_ptx(
+                lambda: None, tuple(), cc=(10, 0, "f")
+            )
+            self.assertIn(".target sm_100f", ptx)
 
 
 @skip_on_cudasim("Compilation unsupported in the simulator")