Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 30 for “"data parallelism"”.
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Data parallelism with hierarchically tiled objects
Exploiting parallelism in modern machines increases the di culty of developing applications. Thus, new abstractions are needed that facilitate parallel programming and at the same time allow the programmer to control performance. Tiling is a very important primitive for controlling both parallelism …
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Simultaneous exploitation of task and data parallelism in regular scientific applications
… simultaneous exploitation of task and data parallelism. Our optimization is implemented as part of the PARADIGM HPF compiler framework and as part of a MATLAB compiler framework we have developed. The intuitive idea behind the optimization is the use of task parallelism to control the …
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Polyhedral Code Transformation for Julia
… is highly dependent on instruction and data parallelism. Instruction parallelism is largely focused on CPU cores and threading, while data parallelism relies on specialized vectors. Single-instruction, multiple-data (SIMD) vectors allow for a single instruction to be executed on multiple …
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Understanding LLM Communictaion
… either high-level metrics or low-level timing data, but lack the operation-level granularity needed to understand communication patterns during training runs. This thesis presents the NCCL Trace Profiler, a novel methodology for fine-grained analysis of network communication during distributed …
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Development of a parallel SAR processor on a Beowulf cluster
… of a Range-Doppler SAR processor. The inherent data parallelism found in SAR data lead to the choice of using master slave parallel processor, where copies of a slave task perform the same tasks on different sets of data. However, the SAR processor that was parallelised needed to implement a …
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Multithreaded Natural Language Processing Tasks
… systems: </p> <p> 1. Implementation of data parallelism to improve performance of lexical analysis and parsing. </p> <p>2. Extended discussion and algorithm of control parallelism to handle parsing conflicts generated by an ambiguous grammar specification by creating separate parsers in …
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Implementing a Persistent Offline Cache Improving Time to First Execution (TTFX) of GPU Code in Julia
… allow users the ability to run code with high data parallelism efficiently on specialized hardware. GPUCompiler.jl provides a GPU compilation process to Julia allowing users to write highly efficient vector operations common in scientific computing. GPUCompiler.jl does not support the same …
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A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois
Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some …
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Building abstractions for fast, secure, reliable computer systems
… systems: detecting net- work defects at the data plane level, exploiting data parallelism in web pages, and formally verifying security invariants in operating system kernels. This dissertation presents the design, implementation, and evaluation of the above systems, and shows that choosing …
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Towards Algorithm Transformation for Temporal Data Mining on GPU
Data Mining allows one to analyze large amounts of data. With increasing amounts of data being collected, more computing power is needed to mine these larger and larger sums of data. The GPU is an excellent piece of hardware with a compelling price to performance ratio and has rapidly risen in …
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Feasibility of Vector Instruction-Set Semantics Using Abstract Monads
… specifies instructions for operating on multiple data elements in a single instruction, which is useful for domains with high levels of data parallelism, such as graphics rendering and machine learning. In this work I examine the question of whether the same prior work can be extended to formalize …
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Domain decomposition based algorithms for some inverse problems
… problem. The algorithms require measurement data within the physical body in order to retrieve the temperature field and the unknown source terms. It is shown that the algorithms can retrieve both the temperature field and the unknown source accurately. Applicability of the algorithms to …
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Optimizations in stream programming for multimedia applications
… regularly process continuous sequences of data and can be naturally represented under the stream programming domain to take take advantage of domain-specific optimizations. Exploiting characteristics specific to multimedia programs can provide further significant impact on performance for …
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Scalable and Productive Data Management for High-Performance Analytics
Advancements in data acquisition technologies across different domains, from genome sequencing to satellite and telescope imaging to large-scale physics simulations, are leading to an exponential growth in dataset sizes. Extracting knowledge from this wealth of data enables scientific discoveries …
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Comparison of distributed training architecture for convolutional neural network in cloud
The rapid growth of data and ever increasing model complexity of deep neural networks (DNNs) have enabled breakthroughs in various artificial intelligence fields such as computer vision, natural language processing and data mining. The training process of the DNN is a computationally intensive …
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Highly parallelized control programming methodologies using multicore CPU and FPGA for highly dynamic multi-DoF mobile robots, applied to the MIT Cheetah
… to achieve a high-frequency synchronization of data processing from a large number of high-bandwidth actuators and sensors. To solve this important problem in robotics, I developed parallelized control programming methodologies that effectively utilize the advantages of modern parallel real-time …
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Functional parallelism: Theoretical foundations and implementation
Thus far, parallelism at the loop level (or data-parallelism) has been almost exclusively the main target of parallelizing compilers. The variety of new parallel architectures and recent progress in interprocedural dependence analysis suggest new directions for the exploitation of parallelism …
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Efficient Verifiable Computation Made Easy
Recent advancements in cloud computing, data privacy, and cryptography have sparked a growing interest in Verifiable Computation (VC) in both industry and academia. In particular, zero-knowledge proof (ZKP) algorithms are gaining rapid traction due to their strong privacy guarantees. However, they …
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Practical analyses and transformations for flow-based parallelism
… Traditional parallel abstractions such as data parallelism and task parallelism, while necessary, do not fully address the needs of today's multi-threaded commercial applications. Emerging applications in the domains of recognition, mining and synthesis (RMS); image and video processing; …
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Design and Evaluation of a Data-distributed Massively Parallel Implementation of a Global Optimization Algorithm---DIRECT
… an efficient, portable, and robust design of a data-distributed massively parallel DIRECT, the deterministic global optimization algorithm widely used in multidisciplinary engineering design, biological science, and physical science applications. The original algorithm is modified to adapt to …
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