Search for dissertations about: "chalmers computer"

Showing result 1 - 5 of 1265 swedish dissertations containing the words chalmers computer.

2. 1. Lock-free Concurrent Search

   Author : Bapi Chatterjee; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Wait-free; Help-aware; Non-blocking; Concurrency; Linearizability; Lock-based; Lock-free-kD-tree; Amortized Complexity; Data Structure; Binary Search Tree; Blocking; Search; Concurrent; kD-tree; Linked-list; Lock-free; Range Search; Language-portable; Help-optimal; Nearest Neighbour Search; Linearizable; Synchronization;

   Abstract : The contemporary computers typically consist of multiple computing cores with high compute power. Such computers make excellent concurrent asynchronous shared memory system. READ MORE

4. 2. Beyond-application datasets and automated fair benchmarking

   Author : Krister Blanch; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; algorithm evaluation; autonomous systems; containerisation; vehicle odometry; Beyond-application datasets; automatic fair benchmarking;

   Abstract : Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. READ MORE

5. 3. Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning

   Author : Muhaddisa Barat Ali; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; glioma subtype classification; convolutional autoencoder; convolutional NN; multi-stream U-Net.; CycleGAN; 1p 19q codeletion; federated learning; IDH mutation; generative adversarial network; Deep learning;

   Abstract : The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. READ MORE

6. 4. Efficient Implementation of Concurrent Data Structures on Multi-core and Many-core Architectures

   Author : Bapi Chatterjee; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Synchronization Primitives; Lock-free Binary search tree; Lock-free; Concurrent Data Structures;

   Abstract : Synchronization of concurrent threads is the central problem in order to design efficient concurrent data-structures. The compute systems widely available in market are increasingly becoming heterogeneous involving multi-core Central Processing Units (CPUs) and many-core Graphics Processing Units (GPUs). READ MORE

7. 5. Explainable and Resource-Efficient Stream Processing Through Provenance and Scheduling

   Author : Dimitrios Palyvos-Giannas; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Data Streaming; Scheduling; Provenance; Stream Processing;

   Abstract : In our era of big data, information is captured at unprecedented volumes and velocities, with technologies such as Cyber-Physical Systems making quick decisions based on the processing of streaming, unbounded datasets. In such scenarios, it can be beneficial to process the data in an online manner, using the stream processing paradigm implemented by Stream Processing Engines (SPEs). READ MORE