Linux Memory Management: Understanding KSM (Kernel Samepage Merging)

In modern computing environments, especially in virtualized systems, efficient memory utilization is critical. One powerful mechanism the Linux kernel uses to optimize memory usage is Kernel Samepage Merging (KSM). This feature enables the system to identify and merge identical memory pages across processes, significantly reducing physical memory consumption. In this comprehensive guide, we’ll explore how KSM works under the hood, its core components, and its impact on system performance.

What Is KSM?

Kernel Samepage Merging (KSM) is a Linux kernel feature designed to reduce memory usage by identifying and merging identical anonymous pages from different processes or within the same process. When multiple applications or virtual machines run similar workloads—such as running the same operating system or identical services—many of their memory pages contain identical data. Instead of storing duplicate copies, KSM consolidates these into a single shared page marked as read-only.

When a process attempts to modify a shared page, the Copy-on-Write (COW) mechanism ensures data integrity by creating a private copy for that process. This allows memory savings without compromising functionality or security.

👉 Discover how advanced memory optimization powers high-performance computing environments.

How KSM Works: Core Mechanism

KSM operates using a background kernel thread called ksmd, which periodically scans user-space memory regions marked as mergeable. The process hinges on two key concepts:

• Anonymous Pages: These are pages not backed by files (e.g., heap or stack memory), which KSM targets for deduplication.
• Write Protection & COW: Once merged, pages become read-only. Any write attempt triggers a page fault, leading to a private copy being created.

Key Components of KSM

To efficiently manage page merging, KSM relies on three primary data structures:

1. rmap_item: Tracks reverse mappings of virtual addresses to physical pages. It links each virtual address to its corresponding memory structure (mm_struct) and supports insertion into search trees.
2. mm_slot: Represents a process’s memory space (mm_struct) registered with KSM for scanning. Each slot maintains a list of rmap_item entries.
3. ksm_scan: A global cursor that tracks the current scanning state, including which process and memory region are being examined.

These structures work together to enable efficient traversal and comparison of candidate pages.

The Role of Stable and Unstable Trees

KSM uses two Red-Black Trees to organize and compare pages:

• Stable Tree: Contains pages confirmed to be identical and already merged. These entries are considered immutable due to write protection.
• Unstable Tree: Holds pages that have passed initial checksum checks but haven’t yet been verified for long-term stability.

KSM avoids false merges by first checking the stable tree. If no match is found, it proceeds to the unstable tree. After each full scan cycle, the unstable tree is flushed and rebuilt to reflect recent changes.

This dual-tree design ensures accuracy while maintaining performance, even when pages change frequently.

Enabling and Controlling KSM

KSM must be explicitly enabled at compile time via CONFIG_KSM=y. Once active, users can control it through sysfs entries located at /sys/kernel/mm/ksm/.

Key tunables include:

• run: Controls KSM operation (0=stopped, 1=running, 2=unmerge all).
• pages_to_scan: Number of pages scanned per iteration.
• sleep_millisecs: Delay between scan cycles.
• pages_shared: Total number of pages currently shared.
• pages_sharing: Number of additional mappings benefiting from shared pages.
• pages_unshared: Pages found unmergeable during scans.

Monitoring these values helps assess KSM efficiency:

• A high pages_sharing / pages_shared ratio indicates effective sharing.
• A rising pages_unshared count may suggest excessive page volatility.

Triggering KSM: The madvise System Call

Applications must explicitly mark memory regions for deduplication using the madvise() system call with one of two flags:

• MADV_MERGEABLE: Informs the kernel that the specified memory range is eligible for merging.
• MADV_UNMERGEABLE: Removes a region from KSM consideration.

Example usage:

madvise(addr, length, MADV_MERGEABLE);

This opt-in model ensures KSM only affects memory areas where deduplication is safe and desired.

👉 Learn how intelligent resource management improves system scalability and efficiency.

Behind the Scenes: The ksmd Kernel Thread

The ksmd thread runs in the background, waking up periodically to scan candidate pages. Its workflow follows this pattern:

1. Wake Up: Triggered either by a timer or an explicit madvise call.
2. Scan Pages: Iterates over registered memory slots and VMA (Virtual Memory Area) regions flagged as VM_MERGEABLE.
3. Check Page Type: Skips non-anonymous pages; focuses only on anonymous mappings.
4. Calculate Checksums: Computes a hash of each page’s content.

5. Compare with Trees:

   • First checks the stable tree for exact matches.
   • If none found, searches the unstable tree using checksums.
6. Attempt Merge: If a match is found, initiates COW-based merging.
7. Update Structures: Adds successful candidates to the stable tree via stable_tree_append.

If no eligible pages are found during a full pass, the associated mm_slot is cleaned up, and scanning continues.

Distinguishing KSM Pages from Regular Anonymous Pages

While both KSM and standard anonymous pages reside in private mappings, they differ in how reverse mapping is handled:

• Regular Anonymous Pages: Use page->index to calculate virtual addresses based on offset within a VMA.
• KSM Pages: Rely on rmap_item->address stored in the stable node’s hash list, allowing multiple unrelated VMAs to map the same physical page.

The kernel uses flags embedded in the page->mapping pointer to differentiate types:

#define PAGE_MAPPING_ANON 1
#define PAGE_MAPPING_KSM  2

Helper macros determine page type:

PageAnon(page)  // True for both anonymous and KSM pages
PageKsm(page)   // True only for KSM pages

This distinction enables correct handling during page faults and reverse mapping walks.

Performance Considerations and Use Cases

KSM shines in environments with high memory redundancy:

• Virtualization Platforms: Multiple VMs running identical guest OS images benefit greatly from page deduplication.
• Container Orchestration: Clusters with replicated microservices see reduced memory footprint.
• Scientific Computing: Parallel jobs with common data structures gain efficiency.

However, KSM isn’t free—it consumes CPU cycles for scanning and checksum computation. Tuning parameters like pages_to_scan and sleep_millisecs helps balance overhead versus savings.

👉 Explore real-world applications of memory optimization in cloud infrastructure.

Frequently Asked Questions (FAQ)

Q: Can KSM merge pages from different NUMA nodes?
A: Yes, if the merge_across_nodes sysfs parameter is enabled. Otherwise, KSM maintains separate trees per NUMA node to preserve locality.

Q: Does KSM affect application performance?
A: Minimally under normal conditions. However, frequent page modifications increase COW events and scanning load. Monitor pages_volatile to detect such cases.

Q: Are file-backed pages eligible for KSM?
A: No. KSM only processes anonymous pages (e.g., heap, stack). File-backed mappings are excluded.

Q: How does KSM handle page migration?
A: Stable nodes track NUMA affinity. During migration, entries are temporarily moved to a separate list until rebalanced.

Q: Can I disable KSM at runtime?
A: Yes. Writing 0 to /sys/kernel/mm/ksm/run stops ksmd, while writing 2 unmerges all existing KSM pages.

Q: Is KSM enabled by default in most distributions?
A: Not always. Some require manual enabling via kernel config or runtime activation through sysfs.

Conclusion

Kernel Samepage Merging is a sophisticated yet practical solution for reducing memory duplication in modern Linux systems. By intelligently identifying and consolidating identical anonymous pages, KSM enhances memory density—especially valuable in virtualized and containerized environments.

Understanding its inner workings—from the dual-tree search strategy to the role of madvise and COW—empowers developers and administrators to leverage KSM effectively while avoiding unnecessary overhead.

Whether you're optimizing a cloud platform or tuning a high-density server setup, KSM remains a cornerstone of efficient Linux memory management.

Core Keywords: KSM, anonymous pages, Copy-on-Write (COW), madvise, MERGEABLE, UNMERGEABLE, memory optimization, page deduplication