13 papers · ranked by Valyu relevance
Haymo Kutschbach
This work introduces a self-optimizing virtual processor (VP) for numerical array programs that shifts parallelization from a manual developer task to a cooperative, agent-like runtime mechanism. Instead of relying on centralized task-graph scheduling, static compiler optimization, or explicitly annotated parallel…
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Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable reference datasets, accurate MLFF architectures, and efficient active learning strategies to enable robust modeling of complex molecular and…
Stavrinides, Georgios L., Karatza, Helen D.
With the explosive growth of big data, workloads tend to get more complex and computationally demanding. Such applications are processed on distributed interconnected resources that are becoming larger in scale and computational capacity. Data-intensive applications may have different degrees of parallelism and must…
Tasmia Jannat, Michael Gowanlock, Satish Puri
The growing volume of data in scientific domains has made spatial query processing increasingly challenging due to high data transfer costs across the memory hierarchy and limited memory bandwidth. To address these bottlenecks and reduce the energy consumed on data movement, this work explores Processing-in-Memory…
Ran Ginosar
I have greatly enjoyed spending many years in studying parallel computing. My journey goes thorough MP-C, PLURAL, Async Plural, HAL, RC64 and more. As a PhD student at Princeton I studied a combination of shared memory and message passing, motivated by algorithms and the ease of programming. While at the Technion, a…
Kenshin Obi, Ryo Yoshinaka, Fujimoto, Hiroshi + 1 more
—In recent years, the complexity and scale of embedded systems, especially in the rapidly developing field of autonomous driving systems, have increased significantly. This has led to the adoption of software and hardware approaches such as Robot Operating System (ROS) 2 and multi-core processors. Traditional manual…
Farzad Razi, Mehran Moghadam, Sercan Aygun, M. Hassan Najafi + 1 more
Today's high-performance architectures are increasingly constrained by data movement latency and energy overhead, as the slowdown of single-core performance scaling coincides with the rise of highly data-intensive workloads. In-memory architectures have emerged as a complementary solution to conventional von Neumann…
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Free radical copolymerization, a crucial industrial technique for synthesizing copolymers from a diverse array of monomers with ease, has played a significant role in advancing human society. However, the journey from small-scale research and development to manufacturing has been hindered by a lack of research into…
Rubén Langarita, Jesús Alastruey-Benedé, Pablo Ibáñez, Santiago Marco‐Sola + 2 more
—Multiple HPC applications are often bottlenecked by compute-intensive kernels implementing complex dependency patterns (data-dependency bound). Traditional general-purpose accelerators struggle to effectively exploit fine-grain parallelism due to limitations in implementing convoluted data-dependency patterns (like…
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Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
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This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
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Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
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Background: Pharmaceutical batch production faces significant scheduling challenges due to operational uncertainties including equipment failures, yield variability, and demand fluctuations. While scheduling heuristics are widely used in practice, their comparative performance under varying uncertainty conditions…