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64bytemultiplication_assembly-x86

This repository contains different methods of doing 64 byte by 64 byte multiplication in x86 Assembly language. Profiles of each method has been mentioned at the end of assembly code in comments showing which method is Fastest and consumes least CPU cycles.

8bit-alu-verilog

This is a verilog file of deployment of an 8-bit ALU for Xilinx-Spartan 6 FPGA

distrbuted_server_system_cpp

This project contains Remote Procedure Calls based Master slave Server system where Master receives user requests and divides it evenly among the slaves. In this case a txt file is provided and master has to return word count of file and instance counts of a searched word. The Master is made to ensure reliability incase a slave server goes down or becomes a straggler, Master is supposed to distribute its tasks to free slaves to provide results to user in timely manner and mask any faults occured.

fyp-smart-hosptial-bed

Description will be added soon

interview_afiniti

mel-training

meta-swupdate

Yocto receipes to generate a swupdate rootfilesystem as initrd

mindbigdata_mindwaves_classification_nn

This project requires experimentation with data and classifiers to see what best suits to distinguish between the sequence of brain signals to predict right outcome using Deep Neural Networks. The data consists of brainwave signals of 2sec length avg. each corresponding to one of the 11 total classes -1 to 9, -1 tells not a number and 0 to 9 specifies 2 digits. This dataset is to be classified for 2 major classifications i.e. 1. Whether someone is thinking about a digit or not. 2. Which exact digit a person is thinking of if thinking of a digit. Previous work Previous Work on this dataset shows a maximum accuracy of 30 to 33% using all of provided dataSets with following lines mentioned in them. “The stimulus is a digit from 0–9. Brain signals are captured when the participant sees and thinks about the exposed stimuli. The data has been captured using Muse headband consisting of 4 channels. Some EEG signals were also captured on random actions and labelled as -1. The brain signals are captured over a course of two years from a single test subject. The reported state of the art accuracy for this dataset is 31.35% [30] for 11-class (0–9 or -1) classification and 98% for binary classification (digit or not).” [1] The best accuracies achieved are mentioned below. I’m currently using 1-D CNN with a batch size of 256 elements with average pooling and at final stages Dense NN with relu as activation function and adam optimizer. This best accuracy achieved by this NN varies between 26-27% whereas accuracy for binary classification varies between 92-95%. Dataset used only comprises of MindWaves Signals from MindBigData Dataset http://mindbigdata.com/opendb/index.html . FOR BEST time performance during learning use Keras_GPU library

multitasking_kernel-dos_assembly-x86

The following Kernel written in x86 assembly allows non-preemptive multitasking on DOS in which there was no concept of threads and multitasking. This assembly code uses advantage of TSR(Terminate and stay resident) and ISR (interrupt service routine) of DOS to make it happen. The kernel maintains a PCB(Process Control Block) and allows Addition and Removal of multiple tasks in it's PCB, once it is run on DOS, tasks can be Paused, Resumed, Added and Removed from PCB utilizing interrupts for multitasking. The repository includes two timers which print on different parts DOS screen to test the multitasking of Multitasking_Kernel.

primedetector_8bit_verilog

This is an implementation of 8 bit prime number detector in VERILOG-HDL for Xilinx Spartan 6 FPGA. This uses the concept of state machine from Theory of Automata (Deterministic Finite Automata) to determine prime number within <=8 cpu cycles which is a pretty fast implementation using the concept of prime numbers that a number is prime if it is not divisible by any prime number less than square root of that prime. So we check for division by primes under 15 (< sq.rt of 255) using their state machines.

remoteprocedurecalls_c_cpp

This Repository Contains Remote Procedure Calls using JSON, ProtoBuffers(Using GRPC) and XML. You'd need to set GRPC in your system prior to usage of protobuf RPC. Use the following link to guide you through the process of setup https://chromium.googlesource.com/external/github.com/grpc/grpc/+/HEAD/BUILDING.md