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Explore efficient automatic differentiation for sparse tensors, leveraging novel DSLs and optimizations to outperform existing frameworks in data-intensive applications.
Explore a novel framework for object-level data management in heterogeneous memory systems, evaluating tiering strategies for performance and efficiency on modern Intel platforms.
Explore cutting-edge software and hardware solutions for sparse machine learning, enhancing efficiency and performance in ML applications.
Explore a compiler pass using polyhedral analysis to optimize loop tiling for DMA-based hardware accelerators, addressing fixed-width transfer limitations.
Explore ISVABI, a software/firmware approach for efficient video analytics using SSD block I/O interface. Learn about its implementation, performance improvements, and real-world applications.
Explore the impact of formal methods on compiling computations involving semiring value multiplication and aggregation in positive algebra over K-relations.
Explore the Sparse Abstract Machine (SAM) for targeting sparse tensor algebra to spatial dataflow accelerators, including its streaming dataflow abstraction and compiler implementation.
Explore a novel lightweight mechanism for optimizing managed application scalability on NUMA systems. Learn about characterization studies, application-agnostic approaches, and performance improvements in managed runtime environments.
Optimize sparse tensor contractions with efficient loop nests and distributed-memory parallelization for improved performance in tensor decomposition and completion tasks.
Explore memory consistency models for program transformations, examining properties between weak and strong models, and their impact on compiler optimizations and concurrent behaviors in shared memory systems.
Explore compiler techniques for efficiently handling structured data, enhancing performance and optimization in programming languages.
Explore a new approach to detecting divergence bugs using forward under-approximating triples. Learn how this logic reasons about infinite loops and recursive calls compositionally.
Explore a novel weakest pre calculus for quantitative hyperproperties, enabling reasoning about hyperquantities in non-deterministic programs and extending hyper Hoare logic.
Explore coverage types and their connection to Incorrectness Logic, integrating underapproximate reasoning within refinement type systems for enhanced program analysis and verification.
Explore high-assurance smart contracts using Hax toolchain and ConCert for embedding, specifying security properties, and verification in Rust.
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