Zobrazeno 1 - 10
of 7 836
pro vyhledávání: '"Memory architecture"'
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
This paper addresses the challenges posed by frequent memory access during simulations of large-scale spiking neural networks involving synaptic plasticity. We focus on the memory accesses performed during a common synaptic plasticity rule since this
Externí odkaz:
https://doaj.org/article/f6f04d64a2fc4aacb0bdc781468da308
Autor:
Se Yeon Jeong, Jaeho Jung, Hyun Kyu Seo, Jae-Seung Jeong, June Hyuk Lee, Gun Hwan Kim, Min Kyu Yang
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 102906- (2024)
With the accelerated development of artificial intelligence-oriented hardware components, research on low-power, high-density memory devices is actively being conducted. Among various memory devices, resistive switching devices with crossbar structur
Externí odkaz:
https://doaj.org/article/031f9ec3fb1f49658bbf3fe0b522c090
Autor:
Dhilleswararao Pudi, Yu Yang, Dimitrios Stathis, Sunil Kumar Prajapati, Srinivas Boppu, Ahmed Hemani, Linga Reddy Cenkeramaddi
Publikováno v:
IEEE Access, Vol 12, Pp 155885-155903 (2024)
Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the lack of good algorithmic libraries. A good algorithmic library
Externí odkaz:
https://doaj.org/article/d5da1297f8574bae87ac797fa1f57b5c
Autor:
Dhilleswararao Pudi, Shivam Malviya, Srinivas Boppu, Yu Yang, Ahmed Hemani, Linga Reddy Cenkeramaddi
Publikováno v:
IEEE Access, Vol 12, Pp 124081-124094 (2024)
Coarse-Grained Reconfigurable Array (CGRA) architectures are potential high-performance and power-efficient platforms. However, mapping applications efficiently on CGRA, which includes scheduling and binding operations on functional units and variabl
Externí odkaz:
https://doaj.org/article/90e050bb4b894cbb8272c59e66c4744d
Publikováno v:
IEEE Access, Vol 12, Pp 13923-13943 (2024)
Associative access is widely used in fundamental microarchitectural components, such as caches and TLBs. However, associative (or content addressable) memories (CAMs) have been traditionally considered too large, too energy-hungry, and not scalable,
Externí odkaz:
https://doaj.org/article/9d453ee2668e4f39baeac80f85127821
Publikováno v:
IEEE Access, Vol 12, Pp 5973-5985 (2024)
Accurate simulation techniques are indispensable to efficiently propose new memory or architectural organizations. As implementing new hardware concepts in real systems is often not feasible, cycle-accurate simulators employed together with certain b
Externí odkaz:
https://doaj.org/article/e0a1066580a34aa98fceefa7d7cdb749
Publikováno v:
Electronics Letters, Vol 60, Iss 8, Pp n/a-n/a (2024)
Abstract This work proposes a storage element (SE) design for in‐memory computing (IMC). Using the proposed SE design, an IMC array has been constructed to enable in‐situ updates of stored weights. Compared with some existing related works which
Externí odkaz:
https://doaj.org/article/2ace69fce89d4e09870a6000fc6f1bb5
Publikováno v:
IET Circuits, Devices and Systems, Vol 17, Iss 4, Pp 205-212 (2023)
Abstract Significant progress has been made in manufacturing emerging technologies in recent years. This progress implemented in‐memory‐computing and neural networks, one of today's hottest research topics. Over time, the need to process complex
Externí odkaz:
https://doaj.org/article/0fd886c7a18a492481ad9b6728fada55
Publikováno v:
IEEE Access, Vol 11, Pp 78726-78736 (2023)
This paper proposes both software and hardware mechanisms based on the near-memory processing (NMP) accelerator to improve the linked list traversal of the in-memory caching. From a software perspective, we propose a simple but an effective mechanism
Externí odkaz:
https://doaj.org/article/a973790e77264e1f903b733a4c9a3a3b
Autor:
Zhang, Da
A significant portion of the memory in servers today is often unused. Our large-scale study of HPC systems finds that more than half of the total memory in active nodes running user jobs are unused for 88% of the time. Google and Azure Cloud studies
Externí odkaz:
http://hdl.handle.net/10919/115570
