antonmks

7 ms·

31.
by antonmks 11y ago
Could be a good idea for Windows 10 - blocking all ads by default, including those delivered through browsers. It could seriously affect and even kill many current and potential Microsoft competitors like Google and Facebook.
32.
by antonmks 11y ago
Sorry if you are misled :-) The program does parses selected fields, there are strings-to-binaries procedures. I tested this approach on multiterabyte files, take a look at my alenka project, it uses the same method to load large CSV files
33.
by antonmks 11y ago
Thrust CUDA calls are synchronous to each other. You can add an explicit synchronization call cudaDeviceSynchronize() and there won't be a difference in results.
34.
by antonmks 11y ago
I used average time for multiple runs, both GPU and CPU benchmarks ran from memory.
35.
by antonmks 11y ago
It should be 750MB, not 750GB. There is no way a single hard drive can read 750GB in 14 seconds.
36.
by antonmks 11y ago
Yes, CPU version can be accelerated as well, depending on availability of SSE extensions.
37.
Show HN: Parsing CSV files with GPU(github.com)
123 points by antonmks 11y ago|60 comments
38.
Accelerating Alenka with gpu and ssd(github.com)
2 points by antonmks 12y ago|0 comments
39.
A simple SQL statement running on monster computers(github.com)
2 points by antonmks 12y ago|0 comments
40.
by antonmks 13y ago
Doesn't look like it uses any kind of vectorized execution. So the only advantage one gets is reduced amount of data to process. It also doesn't mention execution on compressed data so it has to decompress the data which doesn&#x2
41.
by antonmks 13y ago
Is it possible to generate the dataset that you used ? I would like to run a benchmark for myself and downloading a 1 TB file from Amazon unfortunately is not an option.
42.
by antonmks 13y ago
More videos : government building takeover in Vinnitsa, Ukraine : http://www.youtube.com/watch?v=vi_B637FCDY
43.
by antonmks 13y ago
Disk time matters only when you read your data first time. The following queries won't have to read from the disk. The compressed data may sit in memory for days and the queries won't touch the disk. Now, if your compressed data d
44.
by antonmks 13y ago
The disk time was subtracted because it is in-memory system and when your compressed datasets fit into memory your disk subsystem hopefully will be irrelevant.
45.
by antonmks 13y ago
Comparing against Impala doesn't change anything, Impala is still well behind even on a cluster with just 600 million records : https://docs.google.com/spreadsheet/ccc?key=0AgQ09vI0R_wIdEV... Your other considera
46.
by antonmks 13y ago
Big advantage of Hadoop is that you do not need to pay license fees which in case of relational databases can reach into tens of thousands dollars. The big disadvantage is that Hadoop is two orders of magnitude slower than relational databa
47.
by antonmks 13y ago
Let's see the reasons why the author of nginx would not be accepted into ycombinator : Strong Russian accent : check Over 40 years old : check No revenue stream : check
48.
by antonmks 13y ago
This is exactly why I wear "do not resuscitate" bracelet. I prefer to go peacefully, without having to spend a few extra years brain-dead in a coma.
49.
SQL on Nvidia GPU vs. SUN Fire (github.com)
1 points by antonmks 15y ago|0 comments
50.
by antonmks 15y ago
For GTX 680 the double precision is actually 1/24 of the single precision so it is closer to 4%. Pretty sad when comparing the performance to similar priced Radeon cards.
51.
by antonmks 15y ago
Here the details : Integers and decimals are both stored as 8 bytes. So one record takes 42 bytes. After compression it takes about 8 bytes ( I use FOR - frame of reference) compression and it works really well with decimal numbers (check
52.
by antonmks 15y ago
By column. FOR(frame of reference) compression for integers and decimals, FOR-DELTA for already sorted columns, dictionary for strings.
53.
by antonmks 15y ago
It is 6 GB for Tesla GPU. PCI Express transfer speed is 5GB/s, with average compression rate averaging 4/1 the speed becomes 20GB/s so transfer speed is not a bottleneck anymore.
54.
by antonmks 15y ago
Thank you ! The data are stored on a disk and only the columns necessary for transformations are brought to GPU. In case the data does not fit into a limited GPU memory, it is processed piece by piece. I tested it on terabyte sized files so
55.
Show HN: my database engine for GPU(sourceforge.net)
364 points by antonmks 15y ago|60 comments