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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Enhancing Sparse Data Processing through Energy-Efficient Heterogeneous Architectures

Vasireddy, Pranathi 12 1900 (has links)
Efficiently processing sparse data is a significant challenge in many high-impact domains, including machine learning, graph analytics, and scientific computing. Sparse data representations, such as compressed sparse row (CSR), often suffer from substantial overheads during indexing and irregular memory access patterns, limiting the performance and scalability of these applications. This research addresses these challenges by exploring innovative hardware solutions to improve the performance and energy efficiency of sparse linear algebra computations. By leveraging specialized ASIC accelerators and RISC cores as processing-in-memory (PIM) units, and optimizing parallel data processing on GPUs, this work seeks to significantly reduce computational bottlenecks and enhance the capabilities of applications that rely on sparse data.

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