Merge tag 'drm-accel-2022-11-22' of https://git.kernel.org/pub/scm/li…

…nux/kernel/git/ogabbay/accel into drm-next

This tag contains the patches that add the new compute acceleration
subsystem, which is part of the DRM subsystem.

The patches:
- Add a new directory at drivers/accel.
- Add a new major (261) for compute accelerators.
- Add a new DRM minor type for compute accelerators.
- Integrate the accel core code with DRM core code.
- Add documentation for the accel subsystem.

Signed-off-by: Dave Airlie <airlied@redhat.com>

some acks from the list (some are in the patch series):
Acked-by: Daniel Stone <daniels@collabora.com>
Acked-by: Sonal Santan <sonal.santan@amd.com>
Acked-by: Maxime Ripard <maxime@cerno.tech>
Acked-by: Jacek Lawrynowicz <jacek.lawrynowicz@linux.intel.com>
Tested-by: Jacek Lawrynowicz <jacek.lawrynowicz@linux.intel.com>
Acked-by: Alex Deucher <alexander.deucher@amd.com>
Acked-by: Thomas Zimmermann <tzimmermann@suse.de>

From: Oded Gabbay <ogabbay@kernel.org>
Link: https://patchwork.freedesktop.org/patch/msgid/20221122112222.GA352082@ogabbay-vm-u20.habana-labs.com

Documentation/accel/index.rst

@@ -0,0 +1,17 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+====================
+Compute Accelerators
+====================
+
+.. toctree::
+   :maxdepth: 1
+
+   introduction
+
+.. only::  subproject and html
+
+   Indices
+   =======
+
+   * :ref:`genindex`

Documentation/accel/introduction.rst

@@ -0,0 +1,110 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+============
+Introduction
+============
+
+The Linux compute accelerators subsystem is designed to expose compute
+accelerators in a common way to user-space and provide a common set of
+functionality.
+
+These devices can be either stand-alone ASICs or IP blocks inside an SoC/GPU.
+Although these devices are typically designed to accelerate
+Machine-Learning (ML) and/or Deep-Learning (DL) computations, the accel layer
+is not limited to handling these types of accelerators.
+
+Typically, a compute accelerator will belong to one of the following
+categories:
+
+- Edge AI - doing inference at an edge device. It can be an embedded ASIC/FPGA,
+  or an IP inside a SoC (e.g. laptop web camera). These devices
+  are typically configured using registers and can work with or without DMA.
+
+- Inference data-center - single/multi user devices in a large server. This
+  type of device can be stand-alone or an IP inside a SoC or a GPU. It will
+  have on-board DRAM (to hold the DL topology), DMA engines and
+  command submission queues (either kernel or user-space queues).
+  It might also have an MMU to manage multiple users and might also enable
+  virtualization (SR-IOV) to support multiple VMs on the same device. In
+  addition, these devices will usually have some tools, such as profiler and
+  debugger.
+
+- Training data-center - Similar to Inference data-center cards, but typically
+  have more computational power and memory b/w (e.g. HBM) and will likely have
+  a method of scaling-up/out, i.e. connecting to other training cards inside
+  the server or in other servers, respectively.
+
+All these devices typically have different runtime user-space software stacks,
+that are tailored-made to their h/w. In addition, they will also probably
+include a compiler to generate programs to their custom-made computational
+engines. Typically, the common layer in user-space will be the DL frameworks,
+such as PyTorch and TensorFlow.
+
+Sharing code with DRM
+=====================
+
+Because this type of devices can be an IP inside GPUs or have similar
+characteristics as those of GPUs, the accel subsystem will use the
+DRM subsystem's code and functionality. i.e. the accel core code will
+be part of the DRM subsystem and an accel device will be a new type of DRM
+device.
+
+This will allow us to leverage the extensive DRM code-base and
+collaborate with DRM developers that have experience with this type of
+devices. In addition, new features that will be added for the accelerator
+drivers can be of use to GPU drivers as well.
+
+Differentiation from GPUs
+=========================
+
+Because we want to prevent the extensive user-space graphic software stack
+from trying to use an accelerator as a GPU, the compute accelerators will be
+differentiated from GPUs by using a new major number and new device char files.
+
+Furthermore, the drivers will be located in a separate place in the kernel
+tree - drivers/accel/.
+
+The accelerator devices will be exposed to the user space with the dedicated
+261 major number and will have the following convention:
+
+- device char files - /dev/accel/accel*
+- sysfs             - /sys/class/accel/accel*/
+- debugfs           - /sys/kernel/debug/accel/accel*/
+
+Getting Started
+===============
+
+First, read the DRM documentation at Documentation/gpu/index.rst.
+Not only it will explain how to write a new DRM driver but it will also
+contain all the information on how to contribute, the Code Of Conduct and
+what is the coding style/documentation. All of that is the same for the
+accel subsystem.
+
+Second, make sure the kernel is configured with CONFIG_DRM_ACCEL.
+
+To expose your device as an accelerator, two changes are needed to
+be done in your driver (as opposed to a standard DRM driver):
+
+- Add the DRIVER_COMPUTE_ACCEL feature flag in your drm_driver's
+  driver_features field. It is important to note that this driver feature is
+  mutually exclusive with DRIVER_RENDER and DRIVER_MODESET. Devices that want
+  to expose both graphics and compute device char files should be handled by
+  two drivers that are connected using the auxiliary bus framework.
+
+- Change the open callback in your driver fops structure to accel_open().
+  Alternatively, your driver can use DEFINE_DRM_ACCEL_FOPS macro to easily
+  set the correct function operations pointers structure.
+
+External References
+===================
+
+email threads
+-------------
+
+* `Initial discussion on the New subsystem for acceleration devices <https://lkml.org/lkml/2022/7/31/83>`_ - Oded Gabbay (2022)
+* `patch-set to add the new subsystem <https://lkml.org/lkml/2022/10/22/544>`_ - Oded Gabbay (2022)
+
+Conference talks
+----------------
+
+* `LPC 2022 Accelerators BOF outcomes summary <https://airlied.blogspot.com/2022/09/accelerators-bof-outcomes-summary.html>`_ - Dave Airlie (2022)

Documentation/admin-guide/devices.txt

@@ -3080,6 +3080,11 @@
 		  ...
 		  255 = /dev/osd255	256th OSD Device
 
+ 261 char	Compute Acceleration Devices
+		  0 = /dev/accel/accel0	First acceleration device
+		  1 = /dev/accel/accel1	Second acceleration device
+		    ...
+
  384-511 char	RESERVED FOR DYNAMIC ASSIGNMENT
 		Character devices that request a dynamic allocation of major
 		number will take numbers starting from 511 and downward,

Documentation/subsystem-apis.rst

@@ -43,6 +43,7 @@ needed).
    input/index
    hwmon/index
    gpu/index
+   accel/index
    security/index
    sound/index
    crypto/index

MAINTAINERS

@@ -6836,6 +6836,15 @@ F:	include/drm/drm*
 F:	include/linux/vga*
 F:	include/uapi/drm/drm*
 
+DRM COMPUTE ACCELERATORS DRIVERS AND FRAMEWORK
+M:	Oded Gabbay <ogabbay@kernel.org>
+L:	dri-devel@lists.freedesktop.org
+S:	Maintained
+C:	irc://irc.oftc.net/dri-devel
+T:	git https://git.kernel.org/pub/scm/linux/kernel/git/ogabbay/accel.git
+F:	Documentation/accel/
+F:	drivers/accel/
+
 DRM DRIVERS FOR ALLWINNER A10
 M:	Maxime Ripard <mripard@kernel.org>
 M:	Chen-Yu Tsai <wens@csie.org>

drivers/Kconfig

@@ -99,6 +99,8 @@ source "drivers/media/Kconfig"
 
 source "drivers/video/Kconfig"
 
+source "drivers/accel/Kconfig"
+
 source "sound/Kconfig"
 
 source "drivers/hid/Kconfig"

drivers/accel/Kconfig

@@ -0,0 +1,24 @@
+# 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
+#
+menuconfig DRM_ACCEL
+	bool "Compute Acceleration Framework"
+	depends on DRM
+	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).