MEP-MAS: A Message Passing Multiprocessor Array for Streaming Applications

This thesis presents the design and implementation of a Chip-Multiprocessor (CMP) targeted at streaming applications(e.g. MPEG, MP3). Streaming applications are applications which can be split into several distinct stages working on data elements in a pipelined fashion. We propose a distributed-memory array (MEP- MAS), where the cores...

Streaming FPGA Based Multiprocessor Architecture for Low latency Medical Image Processing

In this work a fast and efficient implementation of a Field Programmable Gate Array (FPGA) based, fixed hardware, streaming multiprocessor architecture for low latency medical image processing is introduced. The design of this computation fabric is based on the ρ-VEX Very Long Instruction Word (VLIW) softcore processor and is in influenced by...

Accelerating Software Pipelines Using Streaming Caches

The trend of increasing performance by parallelism is followed by the adoption of heterogeneous systems. In order to allow more fine-tuned balancing between used thread- and instruction level parallelism, the heterogeneous ρ-VEX platform was developed. Pipelining has been a part of microprocessor development for decades to increase throughput of...

Feeding High-Bandwidth Streaming-Based FPGA Accelerators

A new class of accelerator interfaces has signi cant implications on system architecture. An order of magnitude more bandwidth forces us to reconsider FPGA design. OpenCAPI is a new interconnect standard that enables attaching FPGAs coherently to a high-bandwidth, low- latency interface. Keeping up with this bandwidth poses new challenges for...

Exploring Convolutional Neural Networks on the ρ-VEX architecture

As machine learning algorithms play an ever increasing role in today's technology, more demands are placed on computational hardware to run these algorithms efficiently. In recent years, Convolutional Neural Networks (CNNs) have become an important part of machine learning applications in areas such as object recognition and detection. In this...

Live streaming via WiFi: Monitoring premature babies

This report describes the implementation of a custom streaming solution from an IP camera to a web browser. The system aims to both provide live video and Video on Demand. This will be used to monitor premature babies in incubators.

Minimizing bandwidth utilization for streaming noisy Monte-Carlo renders: For the 2018 individual research pilot

<br/>This study focuses on the question how the bandwidth utilization of a high-quality video-stream from the Exposure Rendering framework can be minimized. Exposure Render uses a Monte-Carlo based rendering system to render volumetric data. The earliest estimation of lighting show high degrees of noise, leading to grainy images before...

Well-being Driven Design: Creating a Meaningful Streaming-platform

People are actively looking to pursue happiness by spending their precious time on meaningful experiences, which are often sought for in media entertainment as it is people’s most engaged in leisure activity today. However, current services fail to support them or even counter them, with their manipulative media-platforms in favor of their goals...

ELM Decision Branching: Improving streaming clustering with decision branching

Clustering is a commonly used method in data analysis. It is a complex problem that can be very time consuming, especially when clustering large datasets with many features. Most clustering algorithms scale exponentially in time when increasing the dataset size, making it infeasible to use them for large datasets. Streaming algorithms do not...

CityREST: CityJSON in A Database + RESTful Access

With the increasing demand for 3D city models in various applications, providing efficient access to 3D city models on the web has become very important and valuable. However, there is a lack of web services in which users can directly and effectively access the city objects contained in the 3D city models on the web. Another problem with web...

Neural Radiance Field (NeRF) as a Rendering Primitive: StreamNeRF - Adapting a NeRF Model for Progressive Decoding

Neural Radiance Fields (NeRF) and their adaptations are known to be computationally intensive during both the training and the evaluating stages. Despite being the end goal, directly rendering a full-resolution representation of the scene is not necessary and not very practical for scenarios like streamed applications. Our goal is to design a...