sched_ext: Maintain an online cid mask in the scheduler arenagrafted

Schedulers on the default cid mapping treat [0, nr_online_cids) as the
online set and restart on hotplug. Schedulers that install their own mapping
with scx_bpf_cid_override() have no way to learn which cids are online: the
count no longer identifies members and the CPU-form cpumask is unusable from
cid programs. This is an obvious hole in the cid API.

Add scx_bpf_online_cmask(), a kernel-maintained cmask in the scheduler's
arena, allocated alongside the per-CPU scratch masks and populated after the
cid mapping is finalized and before ops.init(), for child schedulers too.
The pointer stays valid through ops.exit() with no reference to take. It is
the arena offset as a void pointer, the same form struct_ops arena arguments
arrive in. The verifier types the void return as a scalar for the program's
arena cast.

The mask follows the SCX hotplug notifications: seeded from cpu_active_mask
and updated before ops.cid_online/offline() runs, so it lags cpu_online_mask
only inside a hotplug transition. Updates walk the scheduler list under the
lock that also serializes unlinking. Reads are live, not atomic snapshots.
Root initialization excludes hotplug.

v2: Reworded the getter kerneldoc (Andrea Righi).

Signed-off-by: Tejun Heo <tj@kernel.org>
Reviewed-by: Andrea Righi <arighi@nvidia.com>

1 files changed, 88 insertions, 0 deletions

diff --git a/Documentation/admin-guide/device-mapper/persistent-data.rst b/Documentation/admin-guide/device-mapper/persistent-data.rst
new file mode 100644
index 000000000..2065c3c5a
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+===============
+Persistent data
+===============
+
+Introduction
+============
+
+The more-sophisticated device-mapper targets require complex metadata
+that is managed in kernel.  In late 2010 we were seeing that various
+different targets were rolling their own data structures, for example:
+
+- Mikulas Patocka's multisnap implementation
+- Heinz Mauelshagen's thin provisioning target
+- Another btree-based caching target posted to dm-devel
+- Another multi-snapshot target based on a design of Daniel Phillips
+
+Maintaining these data structures takes a lot of work, so if possible
+we'd like to reduce the number.
+
+The persistent-data library is an attempt to provide a re-usable
+framework for people who want to store metadata in device-mapper
+targets.  It's currently used by the thin-provisioning target and an
+upcoming hierarchical storage target.
+
+Overview
+========
+
+The main documentation is in the header files which can all be found
+under drivers/md/persistent-data.
+
+The block manager
+-----------------
+
+dm-block-manager.[hc]
+
+This provides access to the data on disk in fixed sized-blocks.  There
+is a read/write locking interface to prevent concurrent accesses, and
+keep data that is being used in the cache.
+
+Clients of persistent-data are unlikely to use this directly.
+
+The transaction manager
+-----------------------
+
+dm-transaction-manager.[hc]
+
+This restricts access to blocks and enforces copy-on-write semantics.
+The only way you can get hold of a writable block through the
+transaction manager is by shadowing an existing block (ie. doing
+copy-on-write) or allocating a fresh one.  Shadowing is elided within
+the same transaction so performance is reasonable.  The commit method
+ensures that all data is flushed before it writes the superblock.
+On power failure your metadata will be as it was when last committed.
+
+The Space Maps
+--------------
+
+dm-space-map.h
+dm-space-map-metadata.[hc]
+dm-space-map-disk.[hc]
+
+On-disk data structures that keep track of reference counts of blocks.
+Also acts as the allocator of new blocks.  Currently two
+implementations: a simpler one for managing blocks on a different
+device (eg. thinly-provisioned data blocks); and one for managing
+the metadata space.  The latter is complicated by the need to store
+its own data within the space it's managing.
+
+The data structures
+-------------------
+
+dm-btree.[hc]
+dm-btree-remove.c
+dm-btree-spine.c
+dm-btree-internal.h
+
+Currently there is only one data structure, a hierarchical btree.
+There are plans to add more.  For example, something with an
+array-like interface would see a lot of use.
+
+The btree is 'hierarchical' in that you can define it to be composed
+of nested btrees, and take multiple keys.  For example, the
+thin-provisioning target uses a btree with two levels of nesting.
+The first maps a device id to a mapping tree, and that in turn maps a
+virtual block to a physical block.
+
+Values stored in the btrees can have arbitrary size.  Keys are always
+64bits, although nesting allows you to use multiple keys.