This thesis explores hardware-software co-design for data-intensive applications, targeting the unification of programming models using open standards and exploring experimental techniques for automated query synthesis, and presents X-BQSR, a holistic redesign of genomic base quality score recalibration pipelines.
This work introduces a novel intermediate representation (IR), grounded in relational algebra and sparse iteration theory, that provides a unified abstraction for data and computation that enables workload-agnostic, end-to-end optimizations across diverse analytics applications.
Moving from quantum research and development to production-grade, fault-tolerant quantum workload execution remains one of the most significant challenges facing quantum platform builders. While Python frameworks have enabled an easy entry point for quantum algorithm design, the low-latency requirements for real-time q...
Joseph K. L. Lee, M. Malekmohammadi, Hong-Sheng Zheng et al.· 0 citations
Modern organizations depend on data platforms that must serve two audiences at once: analytical workloads that expect consistent, well-governed tables, and artificial intelligence (AI) workloads that expect fresh, versioned, feature-ready data delivered to training and inference systems. Most platforms were not designe...
Santoshi Maddali· World Journal of Advanced Re...· 0 citations
The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system.
Youngjun Lee, Klaus Weide, Wesley Kwiecinski et al.· The international journal of...· 1 citation
It is demonstrated that LLMs provided with specific optimization goals achieve better measured performance and validity rates when generating C code compared to creating computation pipelines and optimization schedules with established frameworks, suggesting that future development should explore alternative approaches...
Jiří Klepl, Matyáš Brabec, Martin Kruliš· 0 citations
Loom, a tuning-free symbolic compiler framework for tile-based SPMD programs on spatial dataflow architectures, is presented, suggesting that hardware-derived symbolic compilation provides a retargetable alternative to profiling-based tuning for spatial dataflow architectures while remaining interpretable by keeping op...
He-Ru Wang, Wei Li, Zhen-Yu Bai et al.· 0 citations
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