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authorFuad Tabba <fuad.tabba@linux.dev>2026-09-22 19:14:30 +0100
committerWill Deacon <will@kernel.org>2026-09-23 12:34:30 +0000
commit2bc6b218717b9d08f466f88209251d54bc09b207 (patch)
treecb91c941eccb15f94cbec4e96aa3a9c8736b5d66 /drivers/accel/Kconfig
downloadlinux-stable-2bc6b218717b9d08f466f88209251d54bc09b207.tar.gz
linux-stable-2bc6b218717b9d08f466f88209251d54bc09b207.zip
arm64/boot: Disable trapping of PMZR_EL0 writes to EL2grafted
__init_el2_fgt2() writes one mask to both HDFGRTR2_EL2 and HDFGWTR2_EL2. PMZR_EL0 is write-only, so its trap bit, nPMZR_EL0, exists only in HDFGWTR2_EL2 and is therefore never set: a PMZR_EL0 write from the host traps to EL2, where the nVHE hypervisor has no handler and BUG()s. The kernel never writes PMZR_EL0, but kernel.perf_user_access=1 has the PMU driver set PMUSERENR_EL0.UEN for a task with a user-read event, so a write from EL0 reaches the trap and takes the host down without a panic message. Accumulate the HDFGWTR2_EL2 bits separately, as __init_el2_fgt() already does for HDFGWTR_EL2, and set nPMZR_EL0 with the other FEAT_PMUv3p9 bits. Fixes: 858c7bfcb35e1 ("arm64/boot: Enable EL2 requirements for FEAT_PMUv3p9") Cc: stable@vger.kernel.org Signed-off-by: Fuad Tabba <fuad.tabba@linux.dev> Reviewed-by: Anshuman Khandual <anshuman.khandual@arm.com> Reviewed-by: Oliver Upton <oupton@kernel.org> Signed-off-by: Will Deacon <will@kernel.org>
Diffstat (limited to 'drivers/accel/Kconfig')
-rw-r--r--drivers/accel/Kconfig34
1 files changed, 34 insertions, 0 deletions
diff --git a/drivers/accel/Kconfig b/drivers/accel/Kconfig
new file mode 100644
index 000000000..bdf48ccaf
--- /dev/null
+++ b/drivers/accel/Kconfig
@@ -0,0 +1,34 @@
+# SPDX-License-Identifier: GPL-2.0-only
+#
+# Compute Acceleration device configuration
+#
+# This framework provides support for compute acceleration devices, such
+# as, but not limited to, Machine-Learning and Deep-Learning acceleration
+# devices
+#
+if DRM
+
+menuconfig DRM_ACCEL
+ bool "Compute Acceleration Framework"
+ help
+ Framework for device drivers of compute acceleration devices, such
+ as, but not limited to, Machine-Learning and Deep-Learning
+ acceleration devices.
+ If you say Y here, you need to select the module that's right for
+ your acceleration device from the list below.
+ This framework is integrated with the DRM subsystem as compute
+ accelerators and GPUs share a lot in common and can use almost the
+ same infrastructure code.
+ Having said that, acceleration devices will have a different
+ major number than GPUs, and will be exposed to user-space using
+ different device files, called accel/accel* (in /dev, sysfs
+ and debugfs).
+
+source "drivers/accel/amdxdna/Kconfig"
+source "drivers/accel/ethosu/Kconfig"
+source "drivers/accel/habanalabs/Kconfig"
+source "drivers/accel/ivpu/Kconfig"
+source "drivers/accel/qaic/Kconfig"
+source "drivers/accel/rocket/Kconfig"
+
+endif