contest 0.50 results to date
And here are my results:
noload:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 128.8 97 0 0 1.01 2.4.19-0.24pre4 [3] 127.4 98 0 0 0.99 2.5.40 [3] 134.4 96 0 0 1.05 2.5.40-nopree [3] 133.7 96 0 0 1.04
process_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 194.1 60 134 40 1.52 2.4.19-0.24pre4 [3] 193.2 60 133 40 1.51 2.5.40 [3] 184.5 70 53 31 1.44 2.5.40-nopree [3] 286.4 45 163 55 2.24
io_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 461.0 28 46 8 3.60 2.4.19-0.24pre4 [3] 235.4 55 26 10 1.84 2.5.40 [3] 293.6 45 25 8 2.29 2.5.40-nopree [3] 269.4 50 20 7 2.10
mem_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 161.1 80 38 2 1.26 2.4.19-0.24pre4 [3] 181.2 76 253 19 1.41 2.5.40 [3] 163.0 80 34 2 1.27 2.5.40-nopree [3] 161.7 80 34 2 1.26
Comments ?
Paolo
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Quoted 23 lines · Paolo Ciarrocchi
And here are my results:
noload:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 128.8 97 0 0 1.01 2.4.19-0.24pre4 [3] 127.4 98 0 0 0.99 2.5.40 [3] 134.4 96 0 0 1.05 2.5.40-nopree [3] 133.7 96 0 0 1.04
process_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 194.1 60 134 40 1.52 2.4.19-0.24pre4 [3] 193.2 60 133 40 1.51 2.5.40 [3] 184.5 70 53 31 1.44 2.5.40-nopree [3] 286.4 45 163 55 2.24
io_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 461.0 28 46 8 3.60 2.4.19-0.24pre4 [3] 235.4 55 26 10 1.84 2.5.40 [3] 293.6 45 25 8 2.29 2.5.40-nopree [3] 269.4 50 20 7 2.10
Quoted 7 lines
mem_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 161.1 80 38 2 1.26 2.4.19-0.24pre4 [3] 181.2 76 253 19 1.41 2.5.40 [3] 163.0 80 34 2 1.27 2.5.40-nopree [3] 161.7 80 34 2 1.26
I think I'm going to have to be reminded what "Loads" and "LCPU" mean, please.
For these sorts of tests, I think system-wide CPU% is an interesting thing to track - both user and system. If it is high then we're doing well - doing real work.
The same isn't necessarily true of the compressed-cache kernel, because it's doing extra work in-kernel, so CPU load comparisons there need to be made with some caution.
Apart from observing overall CPU occupancy, we also need to monitor fairness - one way of doing that is to measure the total kernel build elapsed time. Another way would be to observe how much actual progress the streaming IO makes during the kernel build.
What is "2.4.19-0.24pre4"?
I'd suggest that more tests be added. Perhaps
- one competing streaming read
- several competing streaming reads
- competing "tar cf foo ./linux"
- competing "tar xf foo"
- competing "ls -lR > /dev/null"
It would be interesting to test -aa kernels as well - Andrea's kernels tend to be well tuned.
Quoted 2 lines · Andrew Morton
Quoted 1 line · Paolo Ciarrocchi
[snip]
Quoted 11 lines
Quoted 7 lines
mem_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [3] 161.1 80 38 2 1.26 2.4.19-0.24pre4 [3] 181.2 76 253 19 1.41 2.5.40 [3] 163.0 80 34 2 1.27 2.5.40-nopree [3] 161.7 80 34 2 1.26I think I'm going to have to be reminded what "Loads" and "LCPU" mean, please.
Quoted 7 lines
For these sorts of tests, I think system-wide CPU% is an interesting thing to track - both user and system. If it is high then we're doing well - doing real work.
The same isn't necessarily true of the compressed-cache kernel, because it's doing extra work in-kernel, so CPU load comparisons there need to be made with some caution.
Agreed.
I guess the scheduling is another important point here. Firstly, this extra work, usually not substantial, may change a little the scheduling in the system.
Secondly, given that compressed cache usually reduces the IO performed by the system, it may change the scheduling depending on how much IO it saves and on what the applications do. For example, mem_load doesn't swap any page when compressed cache is enabled (those data are highly compressible), turning out to use most of its CPU time slice. In vanilla, mem_load is scheduled all the time to service page faults.
Signature · 1 line
Rodrigo
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Quoted 4 lines · Andrew Morton
Quoted 1 line · Paolo Ciarrocchi
And here are my results:
I think I'm going to have to be reminded what "Loads" and "LCPU" mean, please.
Loads for process_load is the number of iterations each load manages to succeed doing divided by 10000. Loads for mem_load is the number of times mem_load manages to access the ram divided by 1000. Loads for io_load is the approximate number of megabytes divided by 100 it writes during the kernel compile. The denominator for loads was chosen to easily represent the data, and also correlates well with significant digits.
LCPU% is the load's cpu% usage while it is running. The load is started 3 seconds before the kernel compile and takes a variable length of time to finish, so it can be more than 100-cpu%
Quoted 3 lines
For these sorts of tests, I think system-wide CPU% is an interesting thing to track - both user and system. If it is high then we're doing well - doing real work.
So total cpu% being used during the kernel compile? The cpu% + lcpu% should be very close to this. However I'm not sure of the most accurate way to find out average total cpu% used during just the kernel compile - suggestion?
Quoted 3 lines
The same isn't necessarily true of the compressed-cache kernel, because it's doing extra work in-kernel, so CPU load comparisons there need to be made with some caution.
That is clear, and also the reason I have a measure of work done by the load as well as just the lcpu% (which by itself is not very helpful).
Quoted 4 lines
Apart from observing overall CPU occupancy, we also need to monitor fairness - one way of doing that is to measure the total kernel build elapsed time. Another way would be to observe how much actual progress the streaming IO makes during the kernel build.
I believe that is what I'm already showing with the time for each load == kernel build time, and loads==io work done.
Quoted 1 line
What is "2.4.19-0.24pre4"?
Latest version of compressed cache. Note that in my testing of cc I used the optional LZO compression.
Quoted 4 lines
I'd suggest that more tests be added. Perhaps
- one competing streaming read
Quoted 8 lines
- several competing streaming reads
- competing "tar cf foo ./linux"
- competing "tar xf foo"
- competing "ls -lR >
/dev/null"
Sure, adding loads is easy enough. Just exactly what to add I wasn't sure about. I'll give those a shot soon.
Quoted 2 lines
It would be interesting to test -aa kernels as well - Andrea's kernels tend to be well tuned.
Where time permits sure.
Regards,
Con.
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load additions to contest
In reply to Andrew Morton-----BEGIN PGP SIGNED MESSAGE-----
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I've added some load conditions to an experimental version of contest
(http://contest.kolivas.net) and here are some of the results I've obtained so far:
First an explanation
The time column shows how long it took to conduct the kernel compile in the presence of the load
The cpu% shows what percentage of the cpu the kernel compile managed to use during compilation
Loads shows how many times the load managed to run while the kernel compile was happening
Lcpu% shows the percentage cpu the load used while running Ratio shows a ratio of kernel compilation time to the reference (2.4.19)
Use a fixed width font to see the tables correctly.
tarc_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 88.0 74 50 25 1.31 2.4.19-cc [1] 86.1 78 51 26 1.28 2.5.38 [1] 91.8 74 46 22 1.37 2.5.39 [1] 94.4 71 58 27 1.41 2.5.40 [1] 95.0 71 59 27 1.41 2.5.40-mm1 [1] 93.8 72 56 26 1.40
This load repeatedly creates a tar of the include directory of the linux kernel. You can see a decrease in performance was visible at 2.5.38 without a concomitant increase in loads, but this improved by 2.5.39.
tarx_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 87.6 74 13 24 1.30 2.4.19-cc [1] 81.5 80 12 24 1.21 2.5.38 [1] 296.5 23 54 28 4.41 2.5.39 [1] 108.2 64 9 12 1.61 2.5.40 [1] 107.0 64 8 11 1.59 2.5.40-mm1 [1] 120.5 58 12 16 1.79
This load repeatedly extracts a tar of the include directory of the linux kernel. A performance boost is noted by the compressed cache kernel consistent with this data being cached better (less IO). 2.5.38 shows very heavy writing and a performance penalty with that. All the 2.5 kernels show worse performance than the 2.4 kernels as the time taken to compile the kernel is longer even though the amount of work done by the load has decreased.
read_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 134.1 54 14 5 2.00 2.4.19-cc [2] 92.5 72 22 20 1.38 2.5.38 [2] 100.5 76 9 5 1.50 2.5.39 [2] 101.3 74 14 6 1.51 2.5.40 [1] 101.5 73 13 5 1.51 2.5.40-mm1 [1] 104.5 74 9 5 1.56
This load repeatedly copies a file the size of the physical memory to /dev/null. Compressed caching shows the performance boost of caching more of this data in physical ram - caveat is that this data would be simple to compress so the advantage is overstated. The 2.5 kernels show equivalent performance at 2.5.38 (time down at the expense of load down) but have better performance at 2.5.39-40 (time down with equivalent load being performed). 2.5.40-mm1 seems to exhibit the same performance as 2.5.38.
lslr_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 83.1 77 34 24 1.24 2.4.19-cc [1] 82.8 79 34 24 1.23 2.5.38 [1] 74.8 89 16 13 1.11 2.5.39 [1] 76.7 88 18 14 1.14 2.5.40 [1] 74.9 89 15 12 1.12 2.5.40-mm1 [1] 76.0 89 15 12 1.13
This load repeatedly does a ls -lR >/dev/null. The performance seems to be overall similar, with the bias towards the kernel compilation being performed sooner.
These were very interesting loads to conduct as suggested by AKPM and depending on the feedback I get I will probably incorporate them into contest.
Comments?
Con
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Re: load additions to contest
Quoted 12 lines · Con Kolivas
...
tarc_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 88.0 74 50 25 1.31 2.4.19-cc [1] 86.1 78 51 26 1.28 2.5.38 [1] 91.8 74 46 22 1.37 2.5.39 [1] 94.4 71 58 27 1.41 2.5.40 [1] 95.0 71 59 27 1.41 2.5.40-mm1 [1] 93.8 72 56 26 1.40
Quoted 3 lines
This load repeatedly creates a tar of the include directory of the linux kernel. You can see a decrease in performance was visible at 2.5.38 without a concomitant increase in loads, but this improved by 2.5.39.
Well the kernel compile took 7% longer, but the tar got 10% more work done. I expect this is a CPU scheduler artifact. The scheduler has changed so much, it's hard to draw any conclusions.
Everything there will be in cache. I'd suggest that you increase the size of the tarball a *lot*, so the two activities are competing for disk.
Quoted 9 lines
tarx_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 87.6 74 13 24 1.30 2.4.19-cc [1] 81.5 80 12 24 1.21 2.5.38 [1] 296.5 23 54 28 4.41 2.5.39 [1] 108.2 64 9 12 1.61 2.5.40 [1] 107.0 64 8 11 1.59 2.5.40-mm1 [1] 120.5 58 12 16 1.79
Quoted 7 lines
This load repeatedly extracts a tar of the include directory of the linux kernel. A performance boost is noted by the compressed cache kernel consistent with this data being cached better (less IO). 2.5.38 shows very heavy writing and a performance penalty with that. All the 2.5 kernels show worse performance than the 2.4 kernels as the time taken to compile the kernel is longer even though the amount of work done by the load has decreased.
hm, that's interesting. I assume the tar file is being extracted into the same place each time? Is tar overwriting the old version, or are you unlinking the destination first?
It would be most interesting to rename the untarred tree, so nothing is getting deleted.
Which filesystem are you using here?
Quoted 9 lines
read_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 134.1 54 14 5 2.00 2.4.19-cc [2] 92.5 72 22 20 1.38 2.5.38 [2] 100.5 76 9 5 1.50 2.5.39 [2] 101.3 74 14 6 1.51 2.5.40 [1] 101.5 73 13 5 1.51 2.5.40-mm1 [1] 104.5 74 9 5 1.56
Quoted 7 lines
This load repeatedly copies a file the size of the physical memory to
/dev/null. Compressed caching shows the performance boost of caching more of this data in physical ram - caveat is that this data would be simple to compress so the advantage is overstated. The 2.5 kernels show equivalent performance at 2.5.38 (time down at the expense of load down) but have better performance at 2.5.39-40 (time down with equivalent load being performed). 2.5.40-mm1 seems to exhibit the same performance as 2.5.38.
That's complex. I expect there's a lot of eviction of executable text happening here. I'm working on tuning that up a bit.
Quoted 9 lines
lslr_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 83.1 77 34 24 1.24 2.4.19-cc [1] 82.8 79 34 24 1.23 2.5.38 [1] 74.8 89 16 13 1.11 2.5.39 [1] 76.7 88 18 14 1.14 2.5.40 [1] 74.9 89 15 12 1.12 2.5.40-mm1 [1] 76.0 89 15 12 1.13
Quoted 3 lines
This load repeatedly does a
ls -lR >/dev/null. The performance seems to be overall similar, with the bias towards the kernel compilation being performed sooner.
How many files were under the `ls -lR'? I'd suggest "zillions", so we get heavily into slab reclaim, and lots of inode and directory cache thrashing and seeking...
Re: load additions to contest
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Quoted 16 lines · Andrew Morton
Quoted 11 lines · Con Kolivas
...
tarc_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 88.0 74 50 25 1.31 2.4.19-cc [1] 86.1 78 51 26 1.28 2.5.38 [1] 91.8 74 46 22 1.37 2.5.39 [1] 94.4 71 58 27 1.41 2.5.40 [1] 95.0 71 59 27 1.41 2.5.40-mm1 [1] 93.8 72 56 26 1.40Quoted 3 lines
This load repeatedly creates a tar of the include directory of the linux kernel. You can see a decrease in performance was visible at 2.5.38 without a concomitant increase in loads, but this improved by 2.5.39.
Quoted 7 lines
Well the kernel compile took 7% longer, but the tar got 10% more work done. I expect this is a CPU scheduler artifact. The scheduler has changed so much, it's hard to draw any conclusions.
Everything there will be in cache. I'd suggest that you increase the size of the tarball a *lot*, so the two activities are competing for disk.
Ok I'll go back to the original idea of tarring the whole kernel directory. It needs to be something constant size obviously.
Quoted 18 lines
Quoted 10 lines
tarx_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 87.6 74 13 24 1.30 2.4.19-cc [1] 81.5 80 12 24 1.21 2.5.38 [1] 296.5 23 54 28 4.41 2.5.39 [1] 108.2 64 9 12 1.61 2.5.40 [1] 107.0 64 8 11 1.59 2.5.40-mm1 [1] 120.5 58 12 16 1.79Quoted 7 lines
This load repeatedly extracts a tar of the include directory of the linux kernel. A performance boost is noted by the compressed cache kernel consistent with this data being cached better (less IO). 2.5.38 shows very heavy writing and a performance penalty with that. All the 2.5 kernels show worse performance than the 2.4 kernels as the time taken to compile the kernel is longer even though the amount of work done by the load has decreased.
Quoted 3 lines
hm, that's interesting. I assume the tar file is being extracted into the same place each time? Is tar overwriting the old version, or are you unlinking the destination first?
Into the same place and overwriting the original.
Quoted 3 lines
It would be most interesting to rename the untarred tree, so nothing is getting deleted.
Ok, this is going to take up a lot of space though.
Quoted 2 lines
Which filesystem are you using here?
ReiserFS (sorry dont have any other hardware/fs to test on)
Quoted 31 lines
Quoted 10 lines
read_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 134.1 54 14 5 2.00 2.4.19-cc [2] 92.5 72 22 20 1.38 2.5.38 [2] 100.5 76 9 5 1.50 2.5.39 [2] 101.3 74 14 6 1.51 2.5.40 [1] 101.5 73 13 5 1.51 2.5.40-mm1 [1] 104.5 74 9 5 1.56Quoted 8 lines
This load repeatedly copies a file the size of the physical memory to
/dev/null. Compressed caching shows the performance boost of caching more of this data in physical ram - caveat is that this data would be simple to compress so the advantage is overstated. The 2.5 kernels show equivalent performance at 2.5.38 (time down at the expense of load down) but have better performance at 2.5.39-40 (time down with equivalent load being performed). 2.5.40-mm1 seems to exhibit the same performance as 2.5.38.That's complex. I expect there's a lot of eviction of executable text happening here. I'm working on tuning that up a bit.
Quoted 9 lines
lslr_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 83.1 77 34 24 1.24 2.4.19-cc [1] 82.8 79 34 24 1.23 2.5.38 [1] 74.8 89 16 13 1.11 2.5.39 [1] 76.7 88 18 14 1.14 2.5.40 [1] 74.9 89 15 12 1.12 2.5.40-mm1 [1] 76.0 89 15 12 1.13
Quoted 7 lines
Quoted 3 lines
This load repeatedly does a
ls -lR >/dev/null. The performance seems to be overall similar, with the bias towards the kernel compilation being performed sooner.How many files were under the `ls -lR'? I'd suggest "zillions", so we get heavily into slab reclaim, and lots of inode and directory cache thrashing and seeking...
The ls -lR was an entire kernel tree (to remain constant between runs). I dont think I can keep it constant and make it much bigger without creating some sort of fake dir tree unless you can suggest a different approach. I guess overall ls -lr / will not be much different in size between runs if you think that would be satisfactory.
Con
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Re: load additions to contest
In reply to Andrew Morton-----BEGIN PGP SIGNED MESSAGE-----
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Here are the modifications as you suggested.
Quoted 12 lines · Andrew Morton
Quoted 11 lines · Con Kolivas
...
tarc_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 88.0 74 50 25 1.31 2.4.19-cc [1] 86.1 78 51 26 1.28 2.5.38 [1] 91.8 74 46 22 1.37 2.5.39 [1] 94.4 71 58 27 1.41 2.5.40 [1] 95.0 71 59 27 1.41 2.5.40-mm1 [1] 93.8 72 56 26 1.40
Quoted 3 lines
Quoted 3 lines
This load repeatedly creates a tar of the include directory of the linux kernel. You can see a decrease in performance was visible at 2.5.38 without a concomitant increase in loads, but this improved by 2.5.39.
tarc_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 106.5 70 1 8 1.59 2.5.38 [1] 97.2 79 1 6 1.45 2.5.39 [1] 91.8 83 1 6 1.37 2.5.40 [1] 96.9 80 1 6 1.44 2.5.40-mm1 [1] 94.4 81 1 6 1.41
This version tars the whole kernel tree. No files are overwritten this time. The results are definitely different, but the resolution in loads makes that value completely unhelpful.
Quoted 25 lines
Well the kernel compile took 7% longer, but the tar got 10% more work done. I expect this is a CPU scheduler artifact. The scheduler has changed so much, it's hard to draw any conclusions.
Everything there will be in cache. I'd suggest that you increase the size of the tarball a *lot*, so the two activities are competing for disk.
Quoted 16 lines
tarx_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 87.6 74 13 24 1.30 2.4.19-cc [1] 81.5 80 12 24 1.21 2.5.38 [1] 296.5 23 54 28 4.41 2.5.39 [1] 108.2 64 9 12 1.61 2.5.40 [1] 107.0 64 8 11 1.59 2.5.40-mm1 [1] 120.5 58 12 16 1.79This load repeatedly extracts a tar of the include directory of the linux kernel. A performance boost is noted by the compressed cache kernel consistent with this data being cached better (less IO). 2.5.38 shows very heavy writing and a performance penalty with that. All the 2.5 kernels show worse performance than the 2.4 kernels as the time taken to compile the kernel is longer even though the amount of work done by the load has decreased.
tarx_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [1] 132.4 55 2 9 1.97 2.5.38 [1] 120.5 63 2 8 1.79 2.5.39 [1] 108.3 69 1 6 1.61 2.5.40 [1] 110.7 68 1 6 1.65 2.5.40-mm1 [1] 191.5 39 3 7 2.85
This version extracts a tar of the whole kernel tree. No files are overwritten this time. Once again the results are very different, and the loads' resolution is almost too low for comparison.
Quoted 28 lines
hm, that's interesting. I assume the tar file is being extracted into the same place each time? Is tar overwriting the old version, or are you unlinking the destination first?
It would be most interesting to rename the untarred tree, so nothing is getting deleted.
Which filesystem are you using here?
Quoted 9 lines
read_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 134.1 54 14 5 2.00 2.4.19-cc [2] 92.5 72 22 20 1.38 2.5.38 [2] 100.5 76 9 5 1.50 2.5.39 [2] 101.3 74 14 6 1.51 2.5.40 [1] 101.5 73 13 5 1.51 2.5.40-mm1 [1] 104.5 74 9 5 1.56Quoted 8 lines
This load repeatedly copies a file the size of the physical memory to
/dev/null. Compressed caching shows the performance boost of caching more of this data in physical ram - caveat is that this data would be simple to compress so the advantage is overstated. The 2.5 kernels show equivalent performance at 2.5.38 (time down at the expense of load down) but have better performance at 2.5.39-40 (time down with equivalent load being performed). 2.5.40-mm1 seems to exhibit the same performance as 2.5.38.
Quoted 15 lines
That's complex. I expect there's a lot of eviction of executable text happening here. I'm working on tuning that up a bit.
Quoted 12 lines
lslr_load:Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [2] 83.1 77 34 24 1.24 2.4.19-cc [1] 82.8 79 34 24 1.23 2.5.38 [1] 74.8 89 16 13 1.11 2.5.39 [1] 76.7 88 18 14 1.14 2.5.40 [1] 74.9 89 15 12 1.12 2.5.40-mm1 [1] 76.0 89 15 12 1.13This load repeatedly does a
ls -lR >/dev/null. The performance seems to be overall similar, with the bias towards the kernel compilation being performed sooner.
lslr_load:
Kernel [runs] Time CPU% Loads LCPU% Ratio 2.4.19 [1] 89.8 77 1 20 1.34 2.5.38 [1] 99.1 71 1 20 1.48 2.5.39 [1] 101.3 70 2 24 1.51 2.5.40 [1] 97.0 72 1 21 1.44 2.5.40-mm1 [1] 96.6 73 1 22 1.44
This version does ls -lR /. Note the balance is swayed toward taking longer to compile the kernel here, and loads' resolution is lost.
Quoted 4 lines
How many files were under the `ls -lR'? I'd suggest "zillions", so we get heavily into slab reclaim, and lots of inode and directory cache thrashing and seeking...
I hope this is helpful in some way. In this guise it would be difficult to release these as a standard part of contest (fast hardware could theoretically use up all the disk space with this). I'm more than happy to conduct personalised tests for linux kernel development as needed though.
Con
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