devcloud

Data-parallel molecular dynamics simulator for Intel oneAPI.

Intel DevCloud for the Edge hands-on workshop contents (Japanese, 日本語版)

Hands-on workshop contents to learn about Intel DevCloud for the Edge

These are face recognition and object detection programs and used as training materials at KC3 2020.

Traballo Final do Mestrado en Computación de Altas Prestacións (High Performance Computing)

Implementation of certain crucial algorithms in the field of reinforcement learning.

Three real-world scenarios given to analyze and optimize their queuing systems. This project demonstrates how to identify the appropriate Intel Hardware types that will work best for the manufacturing, and retail, and transportation scenarios. This application uses Intel DevCloud.

The main focus area of this project is to propose a possible hardware solution for each scenario. Build out the application and test its performance on the DevCloud using multiple hardware types. Compare the performance to see which hardware performed best.

Plotting a Direction Field with Python (Intel® DevMesh Project)

Deploy custom queuing AI systems for the retail, manufacturing and transportation scenarios and use the Intel® DevCloud to test solutions performance.

vector-add scripts using oneAPI and targeting FPGA devices. Verifications made on Intel's devcloud.

In today’s fast-paced world, technology’s impact extends far beyond convenience. It has now ventured into the realm of mental health, offering novel solutions to age-old challenges.

SynapSys — An enterprise-grade, modular orchestration engine for defining, executing, and monitoring intelligent agentic workflows. Designed to power complex multi-agent systems with memory, guardrails, and observability — using Apache Kafka, Airflow, and Intel® OpenVINO™ for optimized performance.

Given real-world scenarios to build a queuing system and the hardware specifications, the user can identify which hardware types work best. The application tested using the Intel® DevCloud.

Breast cancer classification using a simple neural network involves training a neural network model to classify breast tissue images as either benign or malignant, based on the features extracted from the images.

Project #2 for Intel's Udacity Nanodegree Program, using Intel's OpenDev Cloud for benchmarking different use case scenarios for deploying OpenVino on edge devices

Here is a quick reference guide on how to utilize the execution queue within the Intel® DevCloud Environment.

Submission for udacity solution to smart queuing system on dev cloud