A lightweight library for CUDA benchmarking, device management and random number generation

A graphics application that shows a ray-tracing scene rendered by the fragment shader on a frame buffer object.

This is a Cuda applied ML Library so that anyone can use GPU Powered ML with Ease in Python.

A comprehensive collection of projects developed for the CS426 - Parallel Computing course at Bilkent University. This repository showcases implementations of various parallel computing techniques and algorithms, highlighting the use of MPI, OMP, CUDA and GPU programming.

A GPU algorithm for enumerating weak pseudomanifolds

CS6023: GPU Programming by Prof. Rupesh Nasre in Spring '25 at IIT Madras.

Comprarison of vector operation using CPU vs GPU using Nvidia Cuda

Solutions to the chapters of the Programming massively parallel processors 3rd and 4th edition edition book. (Some answers may be incorrect)

A basic raytracer in C.

A C++ implementation of GPU accelerated Image Processing for conversion of any color image into its greyscale version.

Upload of CUDA programs developed in my GPU Computing Course

A parallel implementation of the K-Nearest neighbors algorithm using CUDA in GPU.

Assignments under the Parallel And Distributed Computing Course

Introduction to PyCuda GPU programming.

CUDA implementation of Multi-Query Attention achieving 97% KV-cache memory reduction for LLM inference, enabling 32x larger batch sizes. Educational project demonstrating CUDA kernel development with PyTorch integration and Llama model benchmarks.

This repository explores the use of GPU parallel processing in the context of Artificial Intelligence (AI), specifically leveraging GPUs for accelerating computations in deep learning tasks.

This repository includes all the code I'll write for practicing and learning parallel computing.

CUDA implementation of "electric" field simulation

Explore performance implications of various matrix multiplication approaches using GPU/CUDA compared to CPU side processing