Sökning: "memory cost"

Visar resultat 1 - 5 av 219 uppsatser innehållade orden memory cost.

1. 1. Optical Communication using Nanowires and Molecular Memory Systems

   Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

   Författare :Thomas Kjellberg Jensen; [2024]
   Nyckelord :neuromorphic computing; nanowire; molecular dye; DASA photoswitch; OBIC; Physics and Astronomy;

   Sammanfattning : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. LÄS MER

3. 2. An evaluation of GPU virtualization

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Josef Vilestad; [2024]
   Nyckelord :gpu; virtualization; mig; siov;

   Sammanfattning : There has been extensive research and progress on virtualization on CPUs for a while. More recently the focus on GPU virtualization has increased as processing power doubles roughly every 2.5 years. Coupled with advances in memory management and the PCIe standard the first hardware assisted virtual solutions became available in the 2010s. LÄS MER

4. 3. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Khalid El Yaacoub; [2024]
   Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER

5. 4. Difference Between Memory-based Storage and Register-based Storage on FPGAs

   Master-uppsats, Linköpings universitet/Institutionen för systemteknik

   Författare :Yiqian Cui; [2023]
   Nyckelord :;

   Sammanfattning : Memory-based storage and register-based storage are commonly used storagetypes in fpgas. This thesis aims to build up the architecture of memory-basedstorage and register-based storage, implement the corresponding methods, compare the difference between them and determine which kind of storage workswell under different circumstances. LÄS MER

7. 5. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Sai Nikhil Boyapati; [2023]
   Nyckelord :Auto-Scaling; Auto-Scaling Recommendations; Cloud Environment; K-Nearest Neighbors; Machine Learning; Recommendation Systems; Random Forests; Support Vector Machines;

   Sammanfattning : Background: Cloud computing’s rapid growth has highlighted the need for efficientresource allocation. While cloud platforms offer scalability and cost-effectiveness for a variety of applications, managing resources to match dynamic workloads remains a challenge. LÄS MER