7 papers · ranked by Valyu relevance
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…
Harry Fitchett, Charles M. Fox
While transistor density is still increasing, clock speeds are not, motivating the search for new parallel architectures. One approach is to completely abandon the concept of CPU – and thus serial imperative programming – and instead to specify and execute tasks in parallel, compiling from programming languages to data…
Zewen Jin, Congkun Ai, Guangpeng Zhang, Hanbo Zhang + 6 more
Modern Mixture-of-Experts (MoE) models increasingly rely on large-scale AI accelerator clusters for efficient training. Ascend NPUs expose heterogeneous on-chip compute resources, including matrix-oriented AIC units and vector-oriented AIV units with explicit cross-queue synchronization support. However, existing…
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…
Shiting Long, Gustavo Ramirez-Hidalgo, Andreas Frommer, Dirk Pleiter
Gauss-Seidel is a well-established iterative method for the solution of linear systems, and multicoloring has been widely used to increase parallelism in iterative solution techniques. Implementing multi-color Gauss-Seidel with conventional divide-and-conquer parallelization strategies, however, may be inefficient due…
Paulo Henrique Leme Ramalho, Dennis Alves Pedersen, Fábio Andrijauskas
The complexity of biomolecular simulations has substantially increased the demand for High-Performance Computing (HPC) infrastructures, particularly in molecular dynamics and coarse-grained modeling. This work presents a systematic performance and scalability analysis of the LAMMPS simulator for coarse-grained…
Zihan Xu, Haolin Tian, Hai Jiang
Large language model (LLM)-driven multi-agent systems typically require multiple model invocations and complex coordination during inference, and their execution strategies directly affect system accuracy, latency, and computational cost. Parallel execution provides a means to improve inference-time efficiency. From…