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Creators/Authors contains: "Brahmakshatriya, Ajay"

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  1. Modern network applications and environments, ranging from data centers and IoT devices to AR/VR headsets and underwater robotics, present diverse requirements that cannot be satisfied by the all or-nothing approach of TCP and UDP protocols. Network researchers and engineers need to create highly tailored protocols targeting individual problem domains. Existing library-based approaches either fall short on the flexibility in features or offer them at a significant performance overhead. To address this challenge, we present NetBlocks, a domain-specific language, and compiler for designing ad-hoc protocols and generating their highly optimized host network stack implementations. NetBlocks DSL input allows users to configure protocols by selecting and customizing features. Unlike other DSL compilers, NetBlocks also allows network researchers to extend the system and add more features easily without any prior compiler knowledge. Our design and implementation employ a high-performance Aspect-Oriented Programming framework written with the staging framework BuildIt. We also introduce a novel Layout Customization Layer that allows staging packet layouts alongside the implementation, which is critical for getting the best performance out of the protocol when possible, while allowing the practitioners to maintain compatibility with existing protocol layers where needed. Our evaluations on three applications ranging across deployments in data centers and underwater acoustic networks demonstrate a trade-off between performance (both latency and throughput) and selected features allowing the user to only pay-for what-they-use. 
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  3. Many graph problems can be solved using ordered parallel graph algorithms that achieve significant speedup over their unordered counterparts by reducing redundant work. This paper introduces a new priority-based extension to GraphIt, a domain-specific language for writing graph applications, to simplify writing high-performance parallel ordered graph algorithms. The extension enables vertices to be processed in a dynamic order while hiding low-level implementation details from the user. We extend the compiler with new program analyses, transformations, and code generation to produce fast implementations of ordered parallel graph algorithms. We also introduce bucket fusion, a new performance optimization that fuses together different rounds of ordered algorithms to reduce synchronization overhead, resulting in 1.2x--3x speedup over the fastest existing ordered algorithm implementations on road networks with large diameters. With the extension, GraphIt achieves up to 3x speedup on six ordered graph algorithms over state-of-the-art frameworks and hand-optimized implementations (Julienne, Galois, and GAPBS) that support ordered algorithms. 
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