Distributed computing is an activity that is performed on a spatially distributed system. An important problem in distributed computing is to provide a user with a non-distributed view of a distributed system to implement a distributed file system that allows the client programmer to ignore the ...
Local feature attribution methods are increasingly used to explain complex machine learning models. However, current methods are limited because they are extremely expensive to compute or are not capable of explaining a distributed series of models where
low-latency open-source inference serving framework for deploying generative AI and reasoning models in large-scale distributed environments. The framework boosts the number of requests served by up to 30x, when running the open-source DeepSeek-R1 models on NVIDIA Blackwell. NVID...
For data parallel computing frameworks, a precise yet useful cost model often measures the job execution time (i.e., beyond simple cost like I/O) [,9,12]. The main challenge in building an execution time based cost model for a DAG workflow is the inherent complexity of system resource al...
Li, “Distributed Inference with Deep Learning Models across Heterogeneous Edge Devices,” in IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, London, United Kingdom: IEEE, May 2022, pp. 330–339. doi: 10.1109/INFOCOM48880.2022.9796896. 1.1 背景 随着深度学习在各种任务中的广泛...
In Proceedings of the Sixth Annual ACM Symposium on Principles of Distributed Computing, PODC ’87 1–12 (Association for Computing Machinery, New York, 1987). Montresor, A. Gossip and Epidemic Protocols 1–15 (John Wiley & Sons, Ltd, 2017). Jelasity, M., Voulgaris, S., Guerraoui, R...
We can guarantee that the system stores the most recently updated data on a single computer. However, in a distributed system, data is shared and replicated across many computing nodes. Consistency is a property of the distributed system, which says that every server should have the same view ...
of research and work need to be done to realize its capabilities and benefits. This review provides an insight into quantum computing models coupled with the identification of some pros and cons. The main contribution of this systematic review is that it summarizes the current state-of-the-art ...
lasso can return fewer than NumLambda fits if the residual error of the fits drops below a threshold fraction of the variance of y. Example: NumLambda=50 Data Types: single | double Options— Options for computing in parallel and setting random streams structure Options for computing in ...
P. Difference in precedence effect between children and adults signifies development of sound localization abilities in complex listening tasks. J. Acoustical Soc. Am. 128, 1979–1991 (2010). Article Google Scholar Santala, O. & Pulkki, V. Directional perception of distributed sound sources. J...