Even wondered how computer is built? And no, I’m not talking about unscrewing your laptop… but exactly how the things happen inside the CPU. If so, then check out TINA from Texas Instruments and open my custom-made all-in-one computer. I spend few weeks preparing this schematic. It contains clock, program counter, memory address register, RAM, ALU, A&B registers, instruction register, microcode decoder, instruction register, address register and program counter. Well that’s a lot ot stuff you need to build 8-bit data and 4-bit address computer, even in simulator. Sample program in my assembly + binary representation, which needs to be
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
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
Today I came back to my OpenCL project (can be found here). I have had not tried it on my fresh Ubuntu 22 installation on my Dell g15 with RTX 3050 Ti. Altough I’ve got NVIDIA driver metapackage installed my program reported that there is some problem with shared library: You can check if the driver is selected in system About window. So there it is in my case, but nvidia-selector command reports that I have nvidia-driver-525 which is weird as drivers tab says I have installed driver 470. On the other hand, running nvidia-smi command says I have enable
Among 3 million public IP address ranges for the whole world, 68k belongs to the Russian Federation. This translates into 45 million addresses. Scanning the HTTP port on this population took 20 hours. I obtained 630k IP addresses with listening on port 80. Of which 530k gives the correct answer of the HTTP type. Only 340k gives an HTTP 200 response. Over 200k run on NGINX servers, and 100k run on Apache. When analyzing the content, you will find GitLab, Kibana, Zabbix or Grafana installations open for registration and use, but also copies of databases, video surveillance systems, etc. My
Programowanie CPU i GPU “Mamy rok 2022. Minęła ponad dekada od pojawienia się OpenCL. Omówię standard, przykładowy sprzęt, a także zaprezentuję rzeczywiste przykłady, które można wykorzystywać obecnie zarówno na historycznym jak i najnowszym sprzęcie, co ma pokazać swego rodzaju uniwersalność tego rozwiązania. Przy okazji zobaczymy jak ewoluowała technologia na przestrzeni ostatnich lat i czy teoria odpowiada praktyce. Udostępnione przykłady pokażą, że dzięki stosowaniu standardu OpenCL możemy uzyskać nawet 50-krotne przyspieszenie działania algorytmu (na korzyść GPU) porównując czas pracy CPU i GPU. Zacznijmy jednak od podstaw, tak aby zrozumieć, dlaczego tak się dzieje…“
Podstawy elektroniki i budowa komputera w symulatorze “Jest to pierwsza część serii Simple High Performance Computing o tytule Podstawy elektroniki i budowa komputera w symulatorze. Swoim zakresem obejmuje zagadnienia związane z elektroniką, a konkretnie jej podstawami, począwszy od pierwotnych zasad fizyki przekładających się na komponenty elektroniczne, z których można budować złożone układy, a finalnie najprostszą obliczeniową maszynę cyfrową. Największy nacisk kładę na praktyczną część zagadnienia, aczkolwiek teoria również jest przedstawiana.“