I’ve been playing around with several devices in a context of running OpenCL code on them. They have one common thing which is excessive heat coming out of GPU and heatsink being unable to dissipate it. I start with MacBookPro3,1. It has NVIDIA 8600M GT, which is known to fail. I assume that it may be linked with overheating. Second example is design failure of Lenovo Thinkpad T420s which has built in NVIDIA NVS 4200M. This laptop has Optimus feature which in theory could detect if workload should be run on discrete or integrated GPU. Unfortunately enabling either Optimus or
Among various computing devices I have there is one that stands out it is NVIDIA Quadro NVS 140M because it supports only FP32 (float) operations, but not FP64 (double). It is generally too old. In OpenCL we have both pow function which takes double and float parameters. The latter is called pown. I use first one to actually benchmark double precision computation. Model Year Core Unit Clk Perf 1k 10k 100k NVS 4200M 2011 48 1 1480 156/12 13 116 1163 Tesla K20xm 2012 2688 14 732 3935/1312 2 3 24 Intel i7 2640M 2011 2 4 2800 n/a 3
You can put your #GPU in #Proxmox server box and pass thru computational power to virtual machines… just in case you would like to run your AI/ML things alongside your virtualized NAS 😀 Finally I got it working. I think so. This Proxmox installation is simple one, just single node for experiments which is half part. The other part is VM configuration. You may ask, what exactly for do I need GPU in VM? I may need because the hardware is capable of running several additional GPUs and I can use all of them at once in different configurations and
You can use OpenStreetMaps on your own hardware. You need to grab map files first, which can be found at https://download.geofabrik.de. Once you downloaded it, install PostgreSQL and enable few extensions: It may be useful at some point later on especially if you would like to try build your own tile server. Next you need to install osm2pgsql and it can be found in system packages in Ubuntu 22. Then: Now give it database password and it will start loading. Depening on hardware it might take from few minutes to tens of hours in case of large files like Europe
Data is valuable if consumed or at least identified. For private and corporate usages I suggest installing Redash as it gives options for saving queries, exporting data, creating visualizations and dashboards and also setting up alerts. There are few other interesting features like creating dropdowns and inputs from saved queries or joining resuls from different data sources thru in-memory SQLite instance. To install Redash, clone the repository. I recommend running Ubuntu 18 LTS server version as it is tested on this distribution. Then chmod a setup.sh file for execution and run it. It will ask for sudo password and going
As already stated in my year 2023 plans, there will be some time for graphics programming. Back in the days I was exploring OpenGL but that was way long ago. Nowadays I think to try something much simpler and accessible like for instance WebGL. This library relies on JavaScript for logic and OpenGL ES for presentation layer. So it is hardware accelerated. But there are some issues with this acceleration. On some computers you can specifically select particular GPU in BIOS/UEFI. However not on every computer. To start with I tried on Lenovo ThinkPad T420s with NVIDIA NVS 4200M. Testing
I’m looking forward for new year’s technology opportunities. I have few ongoing projects which I would like to finish by the end of this year. Here is some brief overview of them: Data Mining chapter of Simple HPC series News feed tool as a subproject for data mining AI/ML project utilizing news feed, OpenCL processing and user-input training Highly portable system monitoring tool for my day-shift Video graphics… most probably WebGL/THREE.js I will try to fit all of these within just around 300 hours available…
OpenCL is excellent in the field of numbers, but not that much into text processing. It lacks even basic functions available in regular C99. So the question is if it is worth trying to process some text in it. In my OpenCL base project (which can be found here) I’ve added “aiml” module. It loads over 31k lines of text with over 4 mln characters. The text itself is in the first buffer of uchar array. Second buffer holds pointers and lenghts of consecutive lines being work-items, so there are over 31k of such work-items. Third buffer is a result
OpenCL implementation od DES cipher is way faster than regular single-threaded C program. 1 mln encryptions take less than a second on RTX 3050 Ti, but also as much as almost 40 seconds on Intel i5-10200h single-thread application. Lack of compact and extremely portable SSL/TLS library in pre C++11 project made me think about going for something easy to implement on my own concerning data encryption. I’ve selected DES, which stands for Data Encryption Standard because of my general understanding of such algorithm. It comes from 1975 and has certain limitations including short key length or known weak keys. But