RE: [dm-devel] Announcement: STEC EnhanceIO SSD caching softwarefor Linux kernel

From: Amit Kale
Date: Fri Jan 18 2013 - 11:23:26 EST



> -----Original Message-----
> From: Jason Warr [mailto:jason@xxxxxxxx]
> Sent: Friday, January 18, 2013 9:26 PM
> To: Amit Kale
> Cc: thornber@xxxxxxxxxx; device-mapper development;
> kent.overstreet@xxxxxxxxx; Mike Snitzer; LKML; linux-
> bcache@xxxxxxxxxxxxxxx
> Subject: Re: [dm-devel] Announcement: STEC EnhanceIO SSD caching
> software for Linux kernel
>
>
> On 01/18/2013 03:08 AM, Amit Kale wrote:
> >> > Can you explain what you mean by that in a little more detail?
> > Let's say latency of a block device is 10ms for 4kB requests. With
> single threaded IO, the throughput will be 4kB/10ms = 400kB/s. If the
> device is capable of more throughput, a multithreaded IO will generate
> more throughput. So with 2 threads the throughput will be roughly
> 800kB/s. We can keep increasing the number of threads resulting in an
> approximately linear throughput. It'll saturate at the maximum capacity
> the device has. So it could saturate at perhaps at 8MB/s. Increasing
> the number of threads beyond this will not increase throughput.
> >
> > This is a simplistic computation. Throughput, latency and number of
> threads are related in a more complex relationship. Latency is still
> important, but throughput is more important.
> >
> > The way all this matters for SSD caching is, caching will typically
> show a higher latency compared to the base SSD, even for a 100% hit
> ratio. It may be possible to reach the maximum throughput achievable
> with the base SSD using a high number of threads. Let's say an SSD
> shows 450MB/s with 4 threads. A cache may show 440MB/s with 8 threads.
> >
> > A practical difficulty in measuring latency is that the latency seen
> by an application is a sum of the device latency plus the time spent in
> request queue (and caching layer, when present). Increasing number of
> threads shows latency increase, although it's only because the requests
> stay in request queue for a longer duration. Latency measurement in a
> multithreaded environment is very challenging. Measurement of
> throughput is fairly straightforward.
> >
> >> >
> >> > As an enterprise level user I see both as important overall.
> >> > However, the biggest driving factor in wanting a cache device in
> >> > front of any sort of target in my use cases is to hide latency as
> >> > the number of threads reading and writing to the backing device go
> >> > up. So for me the cache is basically a tier stage where your
> >> > ability to keep dirty blocks on it is determined by the specific
> use case.
> > SSD caching will help in this case since SSD's latency remains almost
> constant regardless of location of data. HDD latency for sequential and
> random IO could vary by a factor of 5 or even much more.
> >
> > Throughput with caching could even be 100 times the HDD throughput
> when using multiple threaded non-sequential IO.
> > -Amit
>
> Thank you for the explanation. In context your reasoning makes more
> sense to me.
>
> If I am understanding you correctly when you refer to throughput your
> speaking more in terms of IOPS than what most people would think of as
> referencing only bit rate.
>
> I would expect a small increase in minimum and average latency when
> adding in another layer that the blocks have to traverse. If my
> minimum and average increase by 20% on most of my workloads, that is
> very acceptable as long as there is a decrease in 95th and 99th
> percentile maximums. I would hope that absolute maximum would decrease
> as well but that is going to be much harder to achieve.
>
> If I can help test and benchmark all three of these solutions please
> ask. I have allot of hardware resources available to me and perhaps I
> can add value from an outsiders perspective.

That'll be great. I have so far marked EIO's status as alpha. Will require a little more functionality testing before performance. Perhaps in a week or so.

-Amit

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