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blockio-uring

This library supports disk I/O operations using the Linux io_uring API. The library supports submitting large batches of I/O operations in one go. It also supports submitting batches from multiple Haskell threads concurrently. The I/O only blocks the calling thread, not all other Haskell threads. In this style, using a combination of batching and concurrency, it is possible to saturate modern SSDs, thus achieving maximum I/O throughput. This is particularly helpful for performing lots of random reads.

The library only supports recent versions of Linux, because it uses the io_uring kernel API. The library only supports disk operations, not socket operations.

Installation

  1. Install liburing version 2.2 or higher. Use your package manager of choice, or clone a recent version of https://github.com/axboe/liburing and install using make install.
  2. Invoke cabal build or cabal run.

Benchmarks

We can compare the I/O performance that can be achieved using library against the best case of what the system can do. The most interesting comparison is for performing random 4k reads, and measuring the IOPS -- the I/O operations per second.

Baseline using fio

We can use the fio (flexible I/O tester) tool to give us a baseline for the best that the system can manage. The repo contains an fio configuration file for a random read benchmark using io_uring, which we can use like so

user@machine:~/blockio-uring$ fio ./benchmark/randread.fio

This will produce a page full of output, like so

  read: IOPS=129k, BW=505MiB/s (529MB/s)(1024MiB/2028msec)
    slat (usec): min=10, max=735, avg=26.51, stdev=12.57
    clat (usec): min=54, max=4455, avg=695.23, stdev=204.80
     lat (usec): min=148, max=4492, avg=721.75, stdev=202.13
    clat percentiles (usec):
     |  1.00th=[  330],  5.00th=[  400], 10.00th=[  461], 20.00th=[  537],
     | 30.00th=[  578], 40.00th=[  627], 50.00th=[  668], 60.00th=[  725],
     | 70.00th=[  775], 80.00th=[  840], 90.00th=[  963], 95.00th=[ 1057],
     | 99.00th=[ 1287], 99.50th=[ 1401], 99.90th=[ 1778], 99.95th=[ 1942],
     | 99.99th=[ 2802]
   bw (  KiB/s): min=515760, max=518656, per=100.00%, avg=517584.00, stdev=1344.43, samples=4
   iops        : min=128940, max=129664, avg=129396.00, stdev=336.11, samples=4
  lat (usec)   : 100=0.01%, 250=0.17%, 500=13.42%, 750=51.94%, 1000=26.72%
  lat (msec)   : 2=7.70%, 4=0.04%, 10=0.01%
  cpu          : usr=18.55%, sys=30.04%, ctx=140673, majf=0, minf=10
  IO depths    : 1=0.0%, 2=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=0.1%, >=64=100.0%
     submit    : 0=0.0%, 4=0.0%, 8=0.0%, 16=0.0%, 32=100.0%, 64=0.0%, >=64=0.0%
     complete  : 0=0.0%, 4=100.0%, 8=0.0%, 16=0.0%, 32=0.0%, 64=0.1%, >=64=0.0%
     issued rwts: total=262144,0,0,0 short=0,0,0,0 dropped=0,0,0,0
     latency   : target=0, window=0, percentile=100.00%, depth=128

The headline number to focus on is the this bit

  read: IOPS=129k

Note that if you run this benchmark again, you'll get different numbers due to caching. See below for the command to dropping caches.

Haskell benchmarks

The bench executable expects two arguments: (1) a test name, either "low" or "high", and (2) a filepath to a data file. For a fair comparison we use the same file generated by fio, ./benchmark/benchfile.0.0. So we can invoke the test as follows:

user@machine:~/blockio-uring$ cabal run bench -- high ./benchmark/benchfile.0.0

This will report something like

High-level API benchmark
Total I/O ops: 262144
Elapsed time:  2.423867756s
IOPS:          108151

Comparing results

We are primarily interested in IOPS.

On the author's laptop the numbers in question are:

  • fio: 129k IOPS
  • High-level Haskell API: 108k IOPS
  • Low-level Haskell API: 117k IOPS

This is with dropping caches before each run.

So as a rough conclusion, we can get about 90% of the maximum IOPS using the low level Haskell API, or about 80% when using the high level API.

For reference, the SSD in the laptop is a "Samsung SSD 970 EVO Plus 250GB" which the manufacturer claims can do 250K IOPS for 4k random reads, at QD32, or only 17k IOPS at QD1. Of course fio gives a more realistic number, including all the overheads that are present in practice (file systems, encrypted block devices etc).

We can get slightly higher performance with fio using direct=1, 140k IOPS, on the same system. This uses Linux O_DIRECT. The same optimisation is available to the Haskell API, but requires opening the files in O_DIRECT mode.

Dropping caches

Remember to drop page caches in between test runs, or reported statistics will be heavily distorted by page cache hits.

One way to drop page caches is to invoke the following:

user@machine:~/blockio-uring$ sudo sysctl -w vm.drop_caches=1