DAMON provides data access monitoring functionality while making the accuracy and the overhead controllable. The fundamental access monitorings require primitives that dependent on and optimized for the target address space. On the other hand, the accuracy and overhead tradeoff mechanism, which is the core of DAMON, is in the pure logic space. DAMON separates the two parts in different layers and defines its interface to allow various low level primitives implementations configurable with the core logic.
Due to this separated design and the configurable interface, users can extend DAMON for any address space by configuring the core logics with appropriate low level primitive implementations. If appropriate one is not provided, users can implement the primitives on their own.
For example, physical memory, virtual memory, swap space, those for specific processes, NUMA nodes, files, and backing memory devices would be supportable. Also, if some architectures or devices support special optimized access check primitives, those will be easily configurable.
Reference Implementations of Address Space Specific Primitives¶
The low level primitives for the fundamental access monitoring are defined in two parts:
Identification of the monitoring target address range for the address space.
Access check of specific address range in the target space.
DAMON currently provides the implementation of the primitives for only the virtual address spaces. Below two subsections describe how it works.
PTE Accessed-bit Based Access Check¶
The implementation for the virtual address space uses PTE Accessed-bit for
basic access checks. It finds the relevant PTE Accessed bit from the address
by walking the page table for the target task of the address. In this way, the
implementation finds and clears the bit for next sampling target address and
checks whether the bit set again after one sampling period. This could disturb
other kernel subsystems using the Accessed bits, namely Idle page tracking and
the reclaim logic. To avoid such disturbances, DAMON makes it mutually
exclusive with Idle page tracking and uses
flags to solve the conflict with the reclaim logic, as Idle page tracking does.
VMA-based Target Address Range Construction¶
Only small parts in the super-huge virtual address space of the processes are mapped to the physical memory and accessed. Thus, tracking the unmapped address regions is just wasteful. However, because DAMON can deal with some level of noise using the adaptive regions adjustment mechanism, tracking every mapping is not strictly required but could even incur a high overhead in some cases. That said, too huge unmapped areas inside the monitoring target should be removed to not take the time for the adaptive mechanism.
For the reason, this implementation converts the complex mappings to three distinct regions that cover every mapped area of the address space. The two gaps between the three regions are the two biggest unmapped areas in the given address space. The two biggest unmapped areas would be the gap between the heap and the uppermost mmap()-ed region, and the gap between the lowermost mmap()-ed region and the stack in most of the cases. Because these gaps are exceptionally huge in usual address spaces, excluding these will be sufficient to make a reasonable trade-off. Below shows this in detail:
<heap> <BIG UNMAPPED REGION 1> <uppermost mmap()-ed region> (small mmap()-ed regions and munmap()-ed regions) <lowermost mmap()-ed region> <BIG UNMAPPED REGION 2> <stack>
Address Space Independent Core Mechanisms¶
Below four sections describe each of the DAMON core mechanisms and the five
regions update interval,
minimum number of regions, and
number of regions.
Access Frequency Monitoring¶
The output of DAMON says what pages are how frequently accessed for a given
duration. The resolution of the access frequency is controlled by setting
sampling interval and
aggregation interval. In detail, DAMON checks
access to each page per
sampling interval and aggregates the results. In
other words, counts the number of the accesses to each page. After each
aggregation interval passes, DAMON calls callback functions that previously
registered by users so that users can read the aggregated results and then
clears the results. This can be described in below simple pseudo-code:
while monitoring_on: for page in monitoring_target: if accessed(page): nr_accesses[page] += 1 if time() % aggregation_interval == 0: for callback in user_registered_callbacks: callback(monitoring_target, nr_accesses) for page in monitoring_target: nr_accesses[page] = 0 sleep(sampling interval)
The monitoring overhead of this mechanism will arbitrarily increase as the size of the target workload grows.
Region Based Sampling¶
To avoid the unbounded increase of the overhead, DAMON groups adjacent pages
that assumed to have the same access frequencies into a region. As long as the
assumption (pages in a region have the same access frequencies) is kept, only
one page in the region is required to be checked. Thus, for each
interval, DAMON randomly picks one page in each region, waits for one
sampling interval, checks whether the page is accessed meanwhile, and
increases the access frequency of the region if so. Therefore, the monitoring
overhead is controllable by setting the number of regions. DAMON allows users
to set the minimum and the maximum number of regions for the trade-off.
This scheme, however, cannot preserve the quality of the output if the assumption is not guaranteed.
Adaptive Regions Adjustment¶
Even somehow the initial monitoring target regions are well constructed to fulfill the assumption (pages in same region have similar access frequencies), the data access pattern can be dynamically changed. This will result in low monitoring quality. To keep the assumption as much as possible, DAMON adaptively merges and splits each region based on their access frequency.
aggregation interval, it compares the access frequencies of
adjacent regions and merges those if the frequency difference is small. Then,
after it reports and clears the aggregated access frequency of each region, it
splits each region into two or three regions if the total number of regions
will not exceed the user-specified maximum number of regions after the split.
In this way, DAMON provides its best-effort quality and minimal overhead while keeping the bounds users set for their trade-off.
Dynamic Target Space Updates Handling¶
The monitoring target address range could dynamically changed. For example, virtual memory could be dynamically mapped and unmapped. Physical memory could be hot-plugged.
As the changes could be quite frequent in some cases, DAMON checks the dynamic
memory mapping changes and applies it to the abstracted target area only for
each of a user-specified time interval (
regions update interval).