linux-stable/include/linux/memory-tiers.h

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mm/demotion: add support for explicit memory tiers Patch series "mm/demotion: Memory tiers and demotion", v15. The current kernel has the basic memory tiering support: Inactive pages on a higher tier NUMA node can be migrated (demoted) to a lower tier NUMA node to make room for new allocations on the higher tier NUMA node. Frequently accessed pages on a lower tier NUMA node can be migrated (promoted) to a higher tier NUMA node to improve the performance. In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy tier-by-tier by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases: * The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) and that should be put into a higher tier. * The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM (e.g. GPU memory) devices, these memory-only HBM NUMA nodes should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. * Also because the current tier hierarchy always puts CPU nodes into the top tier, when a CPU is hot-added (or hot-removed) and triggers a memory node from CPU-less into a CPU node (or vice versa), the memory tier hierarchy gets changed, even though no memory node is added or removed. This can make the tier hierarchy unstable and make it difficult to support tier-based memory accounting. * A higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), and has resulted in the feature request for an interface to override the system-wide, per-node demotion order from the userspace. This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series make the creation of memory tiers explicit under the control of device driver. Memory Tier Initialization ========================== Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. By default, all memory nodes are assigned to the default tier with abstract distance 512. A device driver can move its memory nodes from the default tier. For example, PMEM can move its memory nodes below the default tier, whereas GPU can move its memory nodes above the default tier. The kernel initialization code makes the decision on which exact tier a memory node should be assigned to based on the requests from the device drivers as well as the memory device hardware information provided by the firmware. Hot-adding/removing CPUs doesn't affect memory tier hierarchy. This patch (of 10): In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases, The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) that should be put into a higher tier. The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM or GPU devices, the memory-only NUMA nodes mapping these devices should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. With current kernel higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series address the above by defining memory tiers explicitly. Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. This patch configures the range/chunk size to be 128. The default DRAM abstract distance is 512. We can have 4 memory tiers below the default DRAM with abstract distance range 0 - 127, 127 - 255, 256- 383, 384 - 511. Faster memory devices can be placed in these faster(higher) memory tiers. Slower memory devices like persistent memory will have abstract distance higher than the default DRAM level. [akpm@linux-foundation.org: fix comment, per Aneesh] Link: https://lkml.kernel.org/r/20220818131042.113280-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-2-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:33 +00:00
/* SPDX-License-Identifier: GPL-2.0 */
#ifndef _LINUX_MEMORY_TIERS_H
#define _LINUX_MEMORY_TIERS_H
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
#include <linux/types.h>
#include <linux/nodemask.h>
#include <linux/kref.h>
mm/demotion: demote pages according to allocation fallback order Currently, a higher tier node can only be demoted to selected nodes on the next lower tier as defined by the demotion path. This strict demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space). This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that currently. This patch adds support to get all the allowed demotion targets for a memory tier. demote_page_list() function is now modified to utilize this allowed node mask as the fallback allocation mask. Link: https://lkml.kernel.org/r/20220818131042.113280-9-aneesh.kumar@linux.ibm.com Signed-off-by: Jagdish Gediya <jvgediya.oss@gmail.com> Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:40 +00:00
#include <linux/mmzone.h>
memory tiering: add abstract distance calculation algorithms management Patch series "memory tiering: calculate abstract distance based on ACPI HMAT", v4. We have the explicit memory tiers framework to manage systems with multiple types of memory, e.g., DRAM in DIMM slots and CXL memory devices. Where, same kind of memory devices will be grouped into memory types, then put into memory tiers. To describe the performance of a memory type, abstract distance is defined. Which is in direct proportion to the memory latency and inversely proportional to the memory bandwidth. To keep the code as simple as possible, fixed abstract distance is used in dax/kmem to describe slow memory such as Optane DCPMM. To support more memory types, in this series, we added the abstract distance calculation algorithm management mechanism, provided a algorithm implementation based on ACPI HMAT, and used the general abstract distance calculation interface in dax/kmem driver. So, dax/kmem can support HBM (high bandwidth memory) in addition to the original Optane DCPMM. This patch (of 4): The abstract distance may be calculated by various drivers, such as ACPI HMAT, CXL CDAT, etc. While it may be used by various code which hot-add memory node, such as dax/kmem etc. To decouple the algorithm users and the providers, the abstract distance calculation algorithms management mechanism is implemented in this patch. It provides interface for the providers to register the implementation, and interface for the users. Multiple algorithm implementations can cooperate via calculating abstract distance for different memory nodes. The preference of algorithm implementations can be specified via priority (notifier_block.priority). Link: https://lkml.kernel.org/r/20230926060628.265989-1-ying.huang@intel.com Link: https://lkml.kernel.org/r/20230926060628.265989-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:25 +00:00
#include <linux/notifier.h>
mm/demotion: add support for explicit memory tiers Patch series "mm/demotion: Memory tiers and demotion", v15. The current kernel has the basic memory tiering support: Inactive pages on a higher tier NUMA node can be migrated (demoted) to a lower tier NUMA node to make room for new allocations on the higher tier NUMA node. Frequently accessed pages on a lower tier NUMA node can be migrated (promoted) to a higher tier NUMA node to improve the performance. In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy tier-by-tier by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases: * The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) and that should be put into a higher tier. * The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM (e.g. GPU memory) devices, these memory-only HBM NUMA nodes should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. * Also because the current tier hierarchy always puts CPU nodes into the top tier, when a CPU is hot-added (or hot-removed) and triggers a memory node from CPU-less into a CPU node (or vice versa), the memory tier hierarchy gets changed, even though no memory node is added or removed. This can make the tier hierarchy unstable and make it difficult to support tier-based memory accounting. * A higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), and has resulted in the feature request for an interface to override the system-wide, per-node demotion order from the userspace. This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series make the creation of memory tiers explicit under the control of device driver. Memory Tier Initialization ========================== Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. By default, all memory nodes are assigned to the default tier with abstract distance 512. A device driver can move its memory nodes from the default tier. For example, PMEM can move its memory nodes below the default tier, whereas GPU can move its memory nodes above the default tier. The kernel initialization code makes the decision on which exact tier a memory node should be assigned to based on the requests from the device drivers as well as the memory device hardware information provided by the firmware. Hot-adding/removing CPUs doesn't affect memory tier hierarchy. This patch (of 10): In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases, The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) that should be put into a higher tier. The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM or GPU devices, the memory-only NUMA nodes mapping these devices should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. With current kernel higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series address the above by defining memory tiers explicitly. Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. This patch configures the range/chunk size to be 128. The default DRAM abstract distance is 512. We can have 4 memory tiers below the default DRAM with abstract distance range 0 - 127, 127 - 255, 256- 383, 384 - 511. Faster memory devices can be placed in these faster(higher) memory tiers. Slower memory devices like persistent memory will have abstract distance higher than the default DRAM level. [akpm@linux-foundation.org: fix comment, per Aneesh] Link: https://lkml.kernel.org/r/20220818131042.113280-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-2-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:33 +00:00
/*
* Each tier cover a abstrace distance chunk size of 128
*/
#define MEMTIER_CHUNK_BITS 7
#define MEMTIER_CHUNK_SIZE (1 << MEMTIER_CHUNK_BITS)
/*
* Smaller abstract distance values imply faster (higher) memory tiers. Offset
* the DRAM adistance so that we can accommodate devices with a slightly lower
* adistance value (slightly faster) than default DRAM adistance to be part of
* the same memory tier.
*/
#define MEMTIER_ADISTANCE_DRAM ((4 * MEMTIER_CHUNK_SIZE) + (MEMTIER_CHUNK_SIZE >> 1))
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
struct memory_tier;
struct memory_dev_type {
/* list of memory types that are part of same tier as this type */
struct list_head tier_sibling;
/* list of memory types that are managed by one driver */
struct list_head list;
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
/* abstract distance for this specific memory type */
int adistance;
/* Nodes of same abstract distance */
nodemask_t nodes;
struct kref kref;
};
acpi, hmat: calculate abstract distance with HMAT A memory tiering abstract distance calculation algorithm based on ACPI HMAT is implemented. The basic idea is as follows. The performance attributes of system default DRAM nodes are recorded as the base line. Whose abstract distance is MEMTIER_ADISTANCE_DRAM. Then, the ratio of the abstract distance of a memory node (target) to MEMTIER_ADISTANCE_DRAM is scaled based on the ratio of the performance attributes of the node to that of the default DRAM nodes. The functions to record the read/write latency/bandwidth of the default DRAM nodes and calculate abstract distance according to read/write latency/bandwidth ratio will be used by CXL CDAT (Coherent Device Attribute Table) and other memory device drivers. So, they are put in memory-tiers.c. Link: https://lkml.kernel.org/r/20230926060628.265989-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:27 +00:00
struct node_hmem_attrs;
#ifdef CONFIG_NUMA
extern bool numa_demotion_enabled;
acpi, hmat: calculate abstract distance with HMAT A memory tiering abstract distance calculation algorithm based on ACPI HMAT is implemented. The basic idea is as follows. The performance attributes of system default DRAM nodes are recorded as the base line. Whose abstract distance is MEMTIER_ADISTANCE_DRAM. Then, the ratio of the abstract distance of a memory node (target) to MEMTIER_ADISTANCE_DRAM is scaled based on the ratio of the performance attributes of the node to that of the default DRAM nodes. The functions to record the read/write latency/bandwidth of the default DRAM nodes and calculate abstract distance according to read/write latency/bandwidth ratio will be used by CXL CDAT (Coherent Device Attribute Table) and other memory device drivers. So, they are put in memory-tiers.c. Link: https://lkml.kernel.org/r/20230926060628.265989-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:27 +00:00
extern struct memory_dev_type *default_dram_type;
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
struct memory_dev_type *alloc_memory_type(int adistance);
void put_memory_type(struct memory_dev_type *memtype);
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
void init_node_memory_type(int node, struct memory_dev_type *default_type);
void clear_node_memory_type(int node, struct memory_dev_type *memtype);
memory tiering: add abstract distance calculation algorithms management Patch series "memory tiering: calculate abstract distance based on ACPI HMAT", v4. We have the explicit memory tiers framework to manage systems with multiple types of memory, e.g., DRAM in DIMM slots and CXL memory devices. Where, same kind of memory devices will be grouped into memory types, then put into memory tiers. To describe the performance of a memory type, abstract distance is defined. Which is in direct proportion to the memory latency and inversely proportional to the memory bandwidth. To keep the code as simple as possible, fixed abstract distance is used in dax/kmem to describe slow memory such as Optane DCPMM. To support more memory types, in this series, we added the abstract distance calculation algorithm management mechanism, provided a algorithm implementation based on ACPI HMAT, and used the general abstract distance calculation interface in dax/kmem driver. So, dax/kmem can support HBM (high bandwidth memory) in addition to the original Optane DCPMM. This patch (of 4): The abstract distance may be calculated by various drivers, such as ACPI HMAT, CXL CDAT, etc. While it may be used by various code which hot-add memory node, such as dax/kmem etc. To decouple the algorithm users and the providers, the abstract distance calculation algorithms management mechanism is implemented in this patch. It provides interface for the providers to register the implementation, and interface for the users. Multiple algorithm implementations can cooperate via calculating abstract distance for different memory nodes. The preference of algorithm implementations can be specified via priority (notifier_block.priority). Link: https://lkml.kernel.org/r/20230926060628.265989-1-ying.huang@intel.com Link: https://lkml.kernel.org/r/20230926060628.265989-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:25 +00:00
int register_mt_adistance_algorithm(struct notifier_block *nb);
int unregister_mt_adistance_algorithm(struct notifier_block *nb);
int mt_calc_adistance(int node, int *adist);
acpi, hmat: calculate abstract distance with HMAT A memory tiering abstract distance calculation algorithm based on ACPI HMAT is implemented. The basic idea is as follows. The performance attributes of system default DRAM nodes are recorded as the base line. Whose abstract distance is MEMTIER_ADISTANCE_DRAM. Then, the ratio of the abstract distance of a memory node (target) to MEMTIER_ADISTANCE_DRAM is scaled based on the ratio of the performance attributes of the node to that of the default DRAM nodes. The functions to record the read/write latency/bandwidth of the default DRAM nodes and calculate abstract distance according to read/write latency/bandwidth ratio will be used by CXL CDAT (Coherent Device Attribute Table) and other memory device drivers. So, they are put in memory-tiers.c. Link: https://lkml.kernel.org/r/20230926060628.265989-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:27 +00:00
int mt_set_default_dram_perf(int nid, struct node_hmem_attrs *perf,
const char *source);
int mt_perf_to_adistance(struct node_hmem_attrs *perf, int *adist);
#ifdef CONFIG_MIGRATION
int next_demotion_node(int node);
mm/demotion: demote pages according to allocation fallback order Currently, a higher tier node can only be demoted to selected nodes on the next lower tier as defined by the demotion path. This strict demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space). This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that currently. This patch adds support to get all the allowed demotion targets for a memory tier. demote_page_list() function is now modified to utilize this allowed node mask as the fallback allocation mask. Link: https://lkml.kernel.org/r/20220818131042.113280-9-aneesh.kumar@linux.ibm.com Signed-off-by: Jagdish Gediya <jvgediya.oss@gmail.com> Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:40 +00:00
void node_get_allowed_targets(pg_data_t *pgdat, nodemask_t *targets);
mm/demotion: update node_is_toptier to work with memory tiers With memory tier support we can have memory only NUMA nodes in the top tier from which we want to avoid promotion tracking NUMA faults. Update node_is_toptier to work with memory tiers. All NUMA nodes are by default top tier nodes. With lower(slower) memory tiers added we consider all memory tiers above a memory tier having CPU NUMA nodes as a top memory tier [sj@kernel.org: include missed header file, memory-tiers.h] Link: https://lkml.kernel.org/r/20220820190720.248704-1-sj@kernel.org [akpm@linux-foundation.org: mm/memory.c needs linux/memory-tiers.h] [aneesh.kumar@linux.ibm.com: make toptier_distance inclusive upper bound of toptiers] Link: https://lkml.kernel.org/r/20220830081457.118960-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-10-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:41 +00:00
bool node_is_toptier(int node);
#else
static inline int next_demotion_node(int node)
{
return NUMA_NO_NODE;
}
mm/demotion: demote pages according to allocation fallback order Currently, a higher tier node can only be demoted to selected nodes on the next lower tier as defined by the demotion path. This strict demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space). This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that currently. This patch adds support to get all the allowed demotion targets for a memory tier. demote_page_list() function is now modified to utilize this allowed node mask as the fallback allocation mask. Link: https://lkml.kernel.org/r/20220818131042.113280-9-aneesh.kumar@linux.ibm.com Signed-off-by: Jagdish Gediya <jvgediya.oss@gmail.com> Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:40 +00:00
static inline void node_get_allowed_targets(pg_data_t *pgdat, nodemask_t *targets)
{
*targets = NODE_MASK_NONE;
}
mm/demotion: update node_is_toptier to work with memory tiers With memory tier support we can have memory only NUMA nodes in the top tier from which we want to avoid promotion tracking NUMA faults. Update node_is_toptier to work with memory tiers. All NUMA nodes are by default top tier nodes. With lower(slower) memory tiers added we consider all memory tiers above a memory tier having CPU NUMA nodes as a top memory tier [sj@kernel.org: include missed header file, memory-tiers.h] Link: https://lkml.kernel.org/r/20220820190720.248704-1-sj@kernel.org [akpm@linux-foundation.org: mm/memory.c needs linux/memory-tiers.h] [aneesh.kumar@linux.ibm.com: make toptier_distance inclusive upper bound of toptiers] Link: https://lkml.kernel.org/r/20220830081457.118960-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-10-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:41 +00:00
static inline bool node_is_toptier(int node)
{
return true;
}
#endif
#else
#define numa_demotion_enabled false
acpi, hmat: calculate abstract distance with HMAT A memory tiering abstract distance calculation algorithm based on ACPI HMAT is implemented. The basic idea is as follows. The performance attributes of system default DRAM nodes are recorded as the base line. Whose abstract distance is MEMTIER_ADISTANCE_DRAM. Then, the ratio of the abstract distance of a memory node (target) to MEMTIER_ADISTANCE_DRAM is scaled based on the ratio of the performance attributes of the node to that of the default DRAM nodes. The functions to record the read/write latency/bandwidth of the default DRAM nodes and calculate abstract distance according to read/write latency/bandwidth ratio will be used by CXL CDAT (Coherent Device Attribute Table) and other memory device drivers. So, they are put in memory-tiers.c. Link: https://lkml.kernel.org/r/20230926060628.265989-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:27 +00:00
#define default_dram_type NULL
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
/*
* CONFIG_NUMA implementation returns non NULL error.
*/
static inline struct memory_dev_type *alloc_memory_type(int adistance)
{
return NULL;
}
static inline void put_memory_type(struct memory_dev_type *memtype)
mm/demotion/dax/kmem: set node's abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE By default, all nodes are assigned to the default memory tier which is the memory tier designated for nodes with DRAM Set dax kmem device node's tier to slower memory tier by assigning abstract distance to MEMTIER_DEFAULT_DAX_ADISTANCE. Low-level drivers like papr_scm or ACPI NFIT can initialize memory device type to a more accurate value based on device tree details or HMAT. If the kernel doesn't find the memory type initialized, a default slower memory type is assigned by the kmem driver. [aneesh.kumar@linux.ibm.com: assign correct memory type for multiple dax devices with the same node affinity] Link: https://lkml.kernel.org/r/20220826100224.542312-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-5-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:36 +00:00
{
}
static inline void init_node_memory_type(int node, struct memory_dev_type *default_type)
{
}
static inline void clear_node_memory_type(int node, struct memory_dev_type *memtype)
{
}
static inline int next_demotion_node(int node)
{
return NUMA_NO_NODE;
}
mm/demotion: demote pages according to allocation fallback order Currently, a higher tier node can only be demoted to selected nodes on the next lower tier as defined by the demotion path. This strict demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space). This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that currently. This patch adds support to get all the allowed demotion targets for a memory tier. demote_page_list() function is now modified to utilize this allowed node mask as the fallback allocation mask. Link: https://lkml.kernel.org/r/20220818131042.113280-9-aneesh.kumar@linux.ibm.com Signed-off-by: Jagdish Gediya <jvgediya.oss@gmail.com> Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:40 +00:00
static inline void node_get_allowed_targets(pg_data_t *pgdat, nodemask_t *targets)
{
*targets = NODE_MASK_NONE;
}
mm/demotion: update node_is_toptier to work with memory tiers With memory tier support we can have memory only NUMA nodes in the top tier from which we want to avoid promotion tracking NUMA faults. Update node_is_toptier to work with memory tiers. All NUMA nodes are by default top tier nodes. With lower(slower) memory tiers added we consider all memory tiers above a memory tier having CPU NUMA nodes as a top memory tier [sj@kernel.org: include missed header file, memory-tiers.h] Link: https://lkml.kernel.org/r/20220820190720.248704-1-sj@kernel.org [akpm@linux-foundation.org: mm/memory.c needs linux/memory-tiers.h] [aneesh.kumar@linux.ibm.com: make toptier_distance inclusive upper bound of toptiers] Link: https://lkml.kernel.org/r/20220830081457.118960-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-10-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:41 +00:00
static inline bool node_is_toptier(int node)
{
return true;
}
memory tiering: add abstract distance calculation algorithms management Patch series "memory tiering: calculate abstract distance based on ACPI HMAT", v4. We have the explicit memory tiers framework to manage systems with multiple types of memory, e.g., DRAM in DIMM slots and CXL memory devices. Where, same kind of memory devices will be grouped into memory types, then put into memory tiers. To describe the performance of a memory type, abstract distance is defined. Which is in direct proportion to the memory latency and inversely proportional to the memory bandwidth. To keep the code as simple as possible, fixed abstract distance is used in dax/kmem to describe slow memory such as Optane DCPMM. To support more memory types, in this series, we added the abstract distance calculation algorithm management mechanism, provided a algorithm implementation based on ACPI HMAT, and used the general abstract distance calculation interface in dax/kmem driver. So, dax/kmem can support HBM (high bandwidth memory) in addition to the original Optane DCPMM. This patch (of 4): The abstract distance may be calculated by various drivers, such as ACPI HMAT, CXL CDAT, etc. While it may be used by various code which hot-add memory node, such as dax/kmem etc. To decouple the algorithm users and the providers, the abstract distance calculation algorithms management mechanism is implemented in this patch. It provides interface for the providers to register the implementation, and interface for the users. Multiple algorithm implementations can cooperate via calculating abstract distance for different memory nodes. The preference of algorithm implementations can be specified via priority (notifier_block.priority). Link: https://lkml.kernel.org/r/20230926060628.265989-1-ying.huang@intel.com Link: https://lkml.kernel.org/r/20230926060628.265989-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:25 +00:00
static inline int register_mt_adistance_algorithm(struct notifier_block *nb)
{
return 0;
}
static inline int unregister_mt_adistance_algorithm(struct notifier_block *nb)
{
return 0;
}
static inline int mt_calc_adistance(int node, int *adist)
{
return NOTIFY_DONE;
}
acpi, hmat: calculate abstract distance with HMAT A memory tiering abstract distance calculation algorithm based on ACPI HMAT is implemented. The basic idea is as follows. The performance attributes of system default DRAM nodes are recorded as the base line. Whose abstract distance is MEMTIER_ADISTANCE_DRAM. Then, the ratio of the abstract distance of a memory node (target) to MEMTIER_ADISTANCE_DRAM is scaled based on the ratio of the performance attributes of the node to that of the default DRAM nodes. The functions to record the read/write latency/bandwidth of the default DRAM nodes and calculate abstract distance according to read/write latency/bandwidth ratio will be used by CXL CDAT (Coherent Device Attribute Table) and other memory device drivers. So, they are put in memory-tiers.c. Link: https://lkml.kernel.org/r/20230926060628.265989-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Tested-by: Bharata B Rao <bharata@amd.com> Reviewed-by: Dave Jiang <dave.jiang@intel.com> Reviewed-by: Alistair Popple <apopple@nvidia.com> Cc: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Cc: Wei Xu <weixugc@google.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Yang Shi <shy828301@gmail.com> Cc: Rafael J Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2023-09-26 06:06:27 +00:00
static inline int mt_set_default_dram_perf(int nid, struct node_hmem_attrs *perf,
const char *source)
{
return -EIO;
}
static inline int mt_perf_to_adistance(struct node_hmem_attrs *perf, int *adist)
{
return -EIO;
}
#endif /* CONFIG_NUMA */
mm/demotion: add support for explicit memory tiers Patch series "mm/demotion: Memory tiers and demotion", v15. The current kernel has the basic memory tiering support: Inactive pages on a higher tier NUMA node can be migrated (demoted) to a lower tier NUMA node to make room for new allocations on the higher tier NUMA node. Frequently accessed pages on a lower tier NUMA node can be migrated (promoted) to a higher tier NUMA node to improve the performance. In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy tier-by-tier by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases: * The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) and that should be put into a higher tier. * The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM (e.g. GPU memory) devices, these memory-only HBM NUMA nodes should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. * Also because the current tier hierarchy always puts CPU nodes into the top tier, when a CPU is hot-added (or hot-removed) and triggers a memory node from CPU-less into a CPU node (or vice versa), the memory tier hierarchy gets changed, even though no memory node is added or removed. This can make the tier hierarchy unstable and make it difficult to support tier-based memory accounting. * A higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), and has resulted in the feature request for an interface to override the system-wide, per-node demotion order from the userspace. This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series make the creation of memory tiers explicit under the control of device driver. Memory Tier Initialization ========================== Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. By default, all memory nodes are assigned to the default tier with abstract distance 512. A device driver can move its memory nodes from the default tier. For example, PMEM can move its memory nodes below the default tier, whereas GPU can move its memory nodes above the default tier. The kernel initialization code makes the decision on which exact tier a memory node should be assigned to based on the requests from the device drivers as well as the memory device hardware information provided by the firmware. Hot-adding/removing CPUs doesn't affect memory tier hierarchy. This patch (of 10): In the current kernel, memory tiers are defined implicitly via a demotion path relationship between NUMA nodes, which is created during the kernel initialization and updated when a NUMA node is hot-added or hot-removed. The current implementation puts all nodes with CPU into the highest tier, and builds the tier hierarchy by establishing the per-node demotion targets based on the distances between nodes. This current memory tier kernel implementation needs to be improved for several important use cases, The current tier initialization code always initializes each memory-only NUMA node into a lower tier. But a memory-only NUMA node may have a high performance memory device (e.g. a DRAM-backed memory-only node on a virtual machine) that should be put into a higher tier. The current tier hierarchy always puts CPU nodes into the top tier. But on a system with HBM or GPU devices, the memory-only NUMA nodes mapping these devices should be in the top tier, and DRAM nodes with CPUs are better to be placed into the next lower tier. With current kernel higher tier node can only be demoted to nodes with shortest distance on the next lower tier as defined by the demotion path, not any other node from any lower tier. This strict, demotion order does not work in all use cases (e.g. some use cases may want to allow cross-socket demotion to another node in the same demotion tier as a fallback when the preferred demotion node is out of space), This demotion order is also inconsistent with the page allocation fallback order when all the nodes in a higher tier are out of space: The page allocation can fall back to any node from any lower tier, whereas the demotion order doesn't allow that. This patch series address the above by defining memory tiers explicitly. Linux kernel presents memory devices as NUMA nodes and each memory device is of a specific type. The memory type of a device is represented by its abstract distance. A memory tier corresponds to a range of abstract distance. This allows for classifying memory devices with a specific performance range into a memory tier. This patch configures the range/chunk size to be 128. The default DRAM abstract distance is 512. We can have 4 memory tiers below the default DRAM with abstract distance range 0 - 127, 127 - 255, 256- 383, 384 - 511. Faster memory devices can be placed in these faster(higher) memory tiers. Slower memory devices like persistent memory will have abstract distance higher than the default DRAM level. [akpm@linux-foundation.org: fix comment, per Aneesh] Link: https://lkml.kernel.org/r/20220818131042.113280-1-aneesh.kumar@linux.ibm.com Link: https://lkml.kernel.org/r/20220818131042.113280-2-aneesh.kumar@linux.ibm.com Signed-off-by: Aneesh Kumar K.V <aneesh.kumar@linux.ibm.com> Reviewed-by: "Huang, Ying" <ying.huang@intel.com> Acked-by: Wei Xu <weixugc@google.com> Cc: Alistair Popple <apopple@nvidia.com> Cc: Bharata B Rao <bharata@amd.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Davidlohr Bueso <dave@stgolabs.net> Cc: Hesham Almatary <hesham.almatary@huawei.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Yang Shi <shy828301@gmail.com> Cc: Jagdish Gediya <jvgediya.oss@gmail.com> Cc: SeongJae Park <sj@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2022-08-18 13:10:33 +00:00
#endif /* _LINUX_MEMORY_TIERS_H */