Zobrazeno 1 - 10
of 24 919
pro vyhledávání: '"Mallik, A"'
Autor:
Mallik, Neeratyoy, Janowski, Maciej, Hog, Johannes, Rakotoarison, Herilalaina, Klein, Aaron, Grabocka, Josif, Hutter, Frank
Scaling model sizes to scale performance has worked remarkably well for the current large language models paradigm. The research and empirical findings of various scaling studies led to novel scaling results and laws that guides subsequent research.
Externí odkaz:
http://arxiv.org/abs/2411.07340
Gate-based quantum computers are an innovative tool for experimentally studying the core principles of quantum mechanics. This work presents the first observation of quantum anomalous heat flow between two qubits and investigates the role of mid-circ
Externí odkaz:
http://arxiv.org/abs/2410.22900
We investigate the path integral of the four-dimensional Einstein-Hilbert gravity for the deSitter-like Universe with fluctuations and study the transition amplitude from one boundary configuration to another for the gravitational system described by
Externí odkaz:
http://arxiv.org/abs/2410.19724
Characterization of the participant-zone (PZ) in the $^{129,124}$Xe + $^{112,124}$Sn reaction at the energy range 65-150 MeV/nucleon reveals copious cluster production. A detailed study of the chemical composition as a function of the impact paramete
Externí odkaz:
http://arxiv.org/abs/2410.11026
Autor:
Mallik, Sameer Kumar
Semiconductor research has shifted towards exploring two-dimensional (2D) materials as candidates for next-generation electronic devices due to the limitations of existing silicon technology. Transition Metal Dichalcogenides (TMDCs) stand out for the
Externí odkaz:
http://arxiv.org/abs/2409.07357
The importance of tuning hyperparameters in Machine Learning (ML) and Deep Learning (DL) is established through empirical research and applications, evident from the increase in new hyperparameter optimization (HPO) algorithms and benchmarks steadily
Externí odkaz:
http://arxiv.org/abs/2408.02533
The design of energy-efficient, high-performance, and reliable Convolutional Neural Network (CNN) accelerators involves significant challenges due to complex power and thermal management issues. This paper introduces SAfEPaTh, a novel system-level ap
Externí odkaz:
http://arxiv.org/abs/2407.17623
The gravitational path-integral of Gauss-Bonnet gravity is investigated and the transition from one spacelike boundary configuration to another is analyzed. Of particular interest is the case of Neumann and Robin boundary conditions which is known to
Externí odkaz:
http://arxiv.org/abs/2407.16692
Autor:
Kundu, Joyjit, Guo, Wenzhe, BanaGozar, Ali, De Alwis, Udari, Sengupta, Sourav, Gupta, Puneet, Mallik, Arindam
Aligning future system design with the ever-increasing compute needs of large language models (LLMs) is undoubtedly an important problem in today's world. Here, we propose a general performance modeling methodology and workload analysis of distribute
Externí odkaz:
http://arxiv.org/abs/2407.14645
Graph games lie at the algorithmic core of many automated design problems in computer science. These are games usually played between two players on a given graph, where the players keep moving a token along the edges according to pre-determined rule
Externí odkaz:
http://arxiv.org/abs/2407.06288