4 research outputs found

    A scalable architecture for ordered parallelism

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    We present Swarm, a novel architecture that exploits ordered irregular parallelism, which is abundant but hard to mine with current software and hardware techniques. In this architecture, programs consist of short tasks with programmer-specified timestamps. Swarm executes tasks speculatively and out of order, and efficiently speculates thousands of tasks ahead of the earliest active task to uncover ordered parallelism. Swarm builds on prior TLS and HTM schemes, and contributes several new techniques that allow it to scale to large core counts and speculation windows, including a new execution model, speculation-aware hardware task management, selective aborts, and scalable ordered commits. We evaluate Swarm on graph analytics, simulation, and database benchmarks. At 64 cores, Swarm achieves 51--122× speedups over a single-core system, and out-performs software-only parallel algorithms by 3--18×.National Science Foundation (U.S.) (Award CAREER-145299

    Hardware support for fine-grained event-driven computation in Anton 2

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    A Computational Study of Amyloid Fibrils and their Structural Properties

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    The term amyloid describes misfolded protein aggregates in which a highly ordered cross β-sheet pattern is adopted. While there exist functional amyloids, the majority of known amyloids are associated with diseases in multicellular organisms. One example is the association is that between Amyloid β (Aβ) and Alzheimer’s disease, a neurodegenerative disorder in humans. Several mechanisms of toxicity have been proposed, yet a lack of dynamic data prevents a full molecular explanation for the toxicity of Aβ and other amyloid systems. Mutational effects often increase the degree of polymorphism in observable structures, compounding the issues with a molecular level examination. In this thesis, Molecular Dynamic (MD) simulations of wild-type and mutant sequences of both Aβ and Prion proteins are performed to explore the structural dynamics of amyloids and amyloid-like systems. The data generated will provide physics-based explanations of the traits of amyloids on a molecular level which may guide further physical experimentation into the mechanism of amyloid toxicity and formation
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