Sökning: "Distributed Matrix Multiplication"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden Distributed Matrix Multiplication.
1. EVALUATION OF THE PERFORMANCE OF WEBGPU IN A CLUSTER OF WEB-BROWSERS FOR SCIENTIFIC COMPUTING
Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : The development and wide spread of Internet browsers and technologies make them a tool that can be used for many scientific problems. This raises the question of whether Internet browsers, together with WebGPU and WebRTC, can be used to do scalable computing in a distributed cluster. LÄS MER
2. Assessing Differences in Precision with Posit Floating Point Format compared to IEEE 754
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Choosing the correct floating point representation can greatly impact the performance and precision of floating point operations. The current floating point representation standard is IEEE 754. A recent floating point representation which seems to yield a greater precision for the same number of bits is called Posit. LÄS MER
3. An Evaluation of TensorFlow as a Programming Framework for HPC Applications
Master-uppsats, KTH/Beräkningsvetenskap och beräkningsteknik (CST); KTH/Parallelldatorcentrum, PDCSammanfattning : In recent years, deep-learning, a branch of machine learning gained increasing popularity due to their extensive applications and performance. At the core of these application is dense matrix-matrix multiplication. Graphics Processing Units (GPUs) are commonly used in the training process due to their massively parallel computation capabilities. LÄS MER
4. Matrix Multiplications on Apache Spark through GPUs
Master-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)Sammanfattning : In this report, we consider the distribution of large scale matrix multiplications across a group of systems through Apache Spark, where each individual system utilizes Graphical Processor Units (GPUs) in order to perform the matrix multiplication. The purpose of this thesis is to research whether the GPU's advantage in performing parallel work can be applied to a distributed environment, and whether it scales noticeably better than a CPU implementation in a distributed environment. LÄS MER
5. Using Map-Reduce for Large Scale Analysis of Graph-Based Data
Master-uppsats, KTH/Skolan för informations- och kommunikationsteknik (ICT)Sammanfattning : As social networks have gained in popularity, maintaining and processing the social network graph information using graph algorithms has become an essential source for discovering potential features of the graph. The escalating size of the social networks has made it impossible to process the huge graphs on a single ma chine in a “real-time” level of execution. LÄS MER
