On Tue, Aug 16, 2022 at 1:10 PM Aneesh Kumar K V <aneesh.kumar@xxxxxxxxxxxxx> wrote: > > On 8/15/22 8:09 AM, Huang, Ying wrote: > > "Aneesh Kumar K.V" <aneesh.kumar@xxxxxxxxxxxxx> writes: > > [snip] > >> > >> +/* > >> + * Default abstract distance assigned to the NUMA node onlined > >> + * by DAX/kmem if the low level platform driver didn't initialize > >> + * one for this NUMA node. > >> + */ > >> +#define MEMTIER_DEFAULT_DAX_ADISTANCE (MEMTIER_ADISTANCE_DRAM * 2) > > > > If my understanding were correct, this is targeting Optane DCPMM for > > now. The measured results in the following paper is, > > > > https://arxiv.org/pdf/2002.06018.pdf > > > > Section: 2.1 Read/Write Latencies > > > > " > > For read access, the latency of DCPMM was 400.1% higher than that of > > DRAM. For write access, it was 407.1% higher. > > " > > > > Section: 2.2 Read/Write Bandwidths > > > > " > > For read access, the throughput of DCPMM was 37.1% of DRAM. For write > > access, it was 7.8% > > " > > > > According to the above data, I think the MEMTIER_DEFAULT_DAX_ADISTANCE > > can be "5 * MEMTIER_ADISTANCE_DRAM". > > > > If we look at mapping every 100% increase in latency as a memory tier, we essentially > will have 4 memory tier here. Each memory tier is covering a range of abstract distance 128. > which makes a total adistance increase from MEMTIER_ADISTANCE_DRAM by 512. This puts > DEFAULT_DAX_DISTANCE at 1024 or MEMTIER_ADISTANCE_DRAM * 2 If my understanding were correct, you are suggesting to use a kind of logarithmic mapping from latency to abstract distance? That is, abstract_distance = log2(latency) While I am suggesting to use a kind of linear mapping from latency to abstract distance. That is, abstract_distance = C * latency I think that linear mapping is easy to understand. Are there some good reasons to use logarithmic mapping? Best Regards, Huang, Ying
