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Intelligent computing: the latest advances, challenges, and future
Computing is a critical driving force in the development of human civilization. In recent years,
we have witnessed the emergence of intelligent computing, a new computing paradigm that …
we have witnessed the emergence of intelligent computing, a new computing paradigm that …
Challenges and trends of SRAM-based computing-in-memory for AI edge devices
When applied to artificial intelligence edge devices, the conventionally von Neumann
computing architecture imposes numerous challenges (eg, improving the energy efficiency) …
computing architecture imposes numerous challenges (eg, improving the energy efficiency) …
C3SRAM: An in-memory-computing SRAM macro based on robust capacitive coupling computing mechanism
This article presents C3SRAM, an in-memory-computing SRAM macro. The macro is an
SRAM module with the circuits embedded in bitcells and peripherals to perform hardware …
SRAM module with the circuits embedded in bitcells and peripherals to perform hardware …
A 64-tile 2.4-Mb in-memory-computing CNN accelerator employing charge-domain compute
Large-scale matrix-vector multiplications, which dominate in deep neural networks (DNNs),
are limited by data movement in modern VLSI technologies. This paper addresses data …
are limited by data movement in modern VLSI technologies. This paper addresses data …
X-SRAM: Enabling in-memory Boolean computations in CMOS static random access memories
Silicon-based static random access memories (SRAM) and digital Boolean logic have been
the workhorse of the state-of-the-art computing platforms. Despite tremendous strides in …
the workhorse of the state-of-the-art computing platforms. Despite tremendous strides in …
A twin-8T SRAM computation-in-memory unit-macro for multibit CNN-based AI edge processors
Computation-in-memory (CIM) is a promising candidate to improve the energy efficiency of
multiply-and-accumulate (MAC) operations of artificial intelligence (AI) chips. This work …
multiply-and-accumulate (MAC) operations of artificial intelligence (AI) chips. This work …
A CMOS-integrated compute-in-memory macro based on resistive random-access memory for AI edge devices
The development of small, energy-efficient artificial intelligence edge devices is limited in
conventional computing architectures by the need to transfer data between the processor …
conventional computing architectures by the need to transfer data between the processor …
8T SRAM cell as a multibit dot-product engine for beyond von Neumann computing
Large-scale digital computing almost exclusively relies on the von Neumann architecture,
which comprises separate units for storage and computations. The energy-expensive …
which comprises separate units for storage and computations. The energy-expensive …
A dual-split 6T SRAM-based computing-in-memory unit-macro with fully parallel product-sum operation for binarized DNN edge processors
Computing-in-memory (CIM) is a promising approach to reduce the latency and improve the
energy efficiency of deep neural network (DNN) artificial intelligence (AI) edge processors …
energy efficiency of deep neural network (DNN) artificial intelligence (AI) edge processors …
IMAC: In-memory multi-bit multiplication and accumulation in 6T SRAM array
In-memory computing'is being widely explored as a novel computing paradigm to mitigate
the well known memory bottleneck. This emerging paradigm aims at embedding some …
the well known memory bottleneck. This emerging paradigm aims at embedding some …