similar to: [PATCH v12 0/7] make balloon pages movable by compaction

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Hi Minchan, [auto build test ERROR on next-20160318] [cannot apply to v4.5-rc7 v4.5-rc6 v4.5-rc5 v4.5] [if your patch is applied to the wrong git tree, please drop us a note to help improving the system] url: https://github.com/0day-ci/linux/commits/Minchan-Kim/Support-non-lru-page-migration/20160321-143339 config: x86_64-randconfig-x000-201612 (attached as .config) reproduce: # save

Hi Minchan, [auto build test ERROR on next-20160318] [cannot apply to v4.5-rc7 v4.5-rc6 v4.5-rc5 v4.5] [if your patch is applied to the wrong git tree, please drop us a note to help improving the system] url: https://github.com/0day-ci/linux/commits/Minchan-Kim/Support-non-lru-page-migration/20160321-143339 config: x86_64-randconfig-x000-201612 (attached as .config) reproduce: # save

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Recently, I got many reports about perfermance degradation in embedded system(Android mobile phone, webOS TV and so on) and easy fork fail. The problem was fragmentation caused by zram and GPU driver mainly. With memory pressure, their pages were spread out all of pageblock and it cannot be migrated with current compaction algorithm which supports only LRU pages. In the end, compaction cannot

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Hello, This series try to enable migration of non-LRU pages, such as driver's page. My ARM-based platform occured severe fragmentation problem after long-term (several days) test. Sometimes even order-3 page allocation failed. It has memory size 512MB ~ 1024MB. 30% ~ 40% memory is consumed for graphic processing and 20~30 memory is reserved for zram. I found that many pages of GPU driver

Hello, This series try to enable migration of non-LRU pages, such as driver's page. My ARM-based platform occured severe fragmentation problem after long-term (several days) test. Sometimes even order-3 page allocation failed. It has memory size 512MB ~ 1024MB. 30% ~ 40% memory is consumed for graphic processing and 20~30 memory is reserved for zram. I found that many pages of GPU driver

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge

Memory fragmentation introduced by ballooning might reduce significantly the number of 2MB contiguous memory blocks that can be used within a guest, thus imposing performance penalties associated with the reduced number of transparent huge pages that could be used by the guest workload. This patch-set follows the main idea discussed at 2012 LSFMMS session: "Ballooning for transparent huge