ACM Journal on Emerging Technologies in Computing Systems

Aims & Scope

The Journal of Emerging Technologies in Computing Systems invites submissions of original technical papers describing research and development in emerging technologies in computing systems.

Major economic and technical challenges are expected to impede the continued scaling of semiconductor devices.

This has resulted in the search for alternate mechanical, biological/biochemical, nanoscale electronic, asynchronous and quantum computing and sensor technologies.

As the underlying nanotechnologies continue to evolve in the labs of chemists, physicists, and biologists, it has become imperative for computer scientists and engineers to translate the potential of the basic building blocks (analogous to the transistor) emerging from these labs into information systems.

Their design will face multiple challenges ranging from the inherent (un)reliability due to the self-assembly nature of the fabrication processes for nanotechnologies, from the complexity due to the sheer volume of nanodevices that will have to be integrated for complex functionality, and from the need to integrate these new nanotechnologies with silicon devices in the same system.

The journal provides comprehensive coverage of innovative work in the specification, design analysis, simulation, verification, testing, and evaluation of computing systems constructed out of emerging technologies and advanced semiconductors

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.6
2024	2.10

Journal Rank

Year	Value
2024	9689

Journal Citation Indicator

Year	Value
2024	487

SJR (SCImago Journal Rank)

Year	Value
2024	0.599

Quartile

Year	Value
2024	Q2

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Engineering and Materials Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Structured Pruning of Deep Convolutional Neural Networks

  Citation: 452

  Authors: Sajid, Kyuyeon, Wonyong

• Spin-transfer torque magnetic random access memory (STT-MRAM)

  Citation: 397

  Authors: Dmytro, Alexey, Steven, Vladimir, Xueti, Daniel, Kiseok, Xiao, Eugene, Adrian, Alexander, Mohamad

• Design space exploration for 3D architectures

  Citation: 244

  Authors: Yuan, Gabriel H., Bryan, Kerry

• A Review, Classification, and Comparative Evaluation of Approximate Arithmetic Circuits

  Citation: 216

  Authors: Honglan, Cong, Leibo, Fabrizio, Jie

• Spiking Neural Networks Hardware Implementations and Challenges

  Citation: 212

  Authors: Maxence, Alexandre, Thomas, Francois, Marina, Elisa, Edith

• Predictive technology model for nano-CMOS design exploration

  Citation: 188

  Authors: Wei, Yu

• Nanowire-based programmable architectures

  Citation: 183

  Authors: André

• A Survey on Chip to System Reverse Engineering

  Citation: 173

  Authors: Shahed E., Junlin, Domenic, Navid, Sina, Lei, John, Mark

• High-level synthesis of digital microfluidic biochips

  Citation: 161

  Authors: Fei, Krishnendu

• A survey of software aging and rejuvenation studies

  Citation: 141

  Authors: Domenico, Roberto, Roberto, Stefano

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