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From:   Alistair Popple <apopple@nvidia.com>
To:     Huang Ying <ying.huang@intel.com>
Cc:     Andrew Morton <akpm@linux-foundation.org>, linux-mm@kvack.org,
        linux-kernel@vger.kernel.org, linux-cxl@vger.kernel.org,
        nvdimm@lists.linux.dev, linux-acpi@vger.kernel.org,
        "Aneesh Kumar K . V" <aneesh.kumar@linux.ibm.com>,
        Wei Xu <weixugc@google.com>,
        Dan Williams <dan.j.williams@intel.com>,
        Dave Hansen <dave.hansen@intel.com>,
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        Johannes Weiner <hannes@cmpxchg.org>,
        Jonathan Cameron <Jonathan.Cameron@huawei.com>,
        Michal Hocko <mhocko@kernel.org>,
        Yang Shi <shy828301@gmail.com>,
        Rafael J Wysocki <rafael.j.wysocki@intel.com>
Subject: Re: [PATCH RESEND 0/4] memory tiering: calculate abstract distance
 based on ACPI HMAT
Date:   Fri, 21 Jul 2023 14:15:31 +1000
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Thanks for this Huang, I had been hoping to take a look at it this week
but have run out of time. I'm keen to do some testing with it as well.

Hopefully next week...

Huang Ying <ying.huang@intel.com> writes:

> 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.
>
> Changelog:
>
> V1 (from RFC):
>
> - Added some comments per Aneesh's comments, Thanks!
>
> Best Regards,
> Huang, Ying