Guest editorial IEEE transactions on emerging topics in special section on emerging in-memory computing architectures and applications
Computer architecture stands at an important crossroad to surmount vital performance challenges. For more than four decades, the performance of general purpose computing systems has been improving by 20-50% per year [1]. In the last decade, this number has dropped to less than 7% per year. Most rece...
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| Main Authors: | , , , |
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| Format: | Article (Journal) Editorial |
| Language: | English |
| Published: |
18 March 2024
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| In: |
IEEE transactions on emerging topics in computing
Year: 2024, Volume: 12, Issue: 1, Pages: 4-6 |
| ISSN: | 2168-6750 |
| DOI: | 10.1109/TETC.2024.3369288 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1109/TETC.2024.3369288 Verlag, lizenzpflichtig, Volltext: https://ieeexplore.ieee.org/document/10474152 
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| Author Notes: | Alberto Bosio, Ronald F. DeMara, Deliang Fan, Nima TaheriNejad |
| Summary: | Computer architecture stands at an important crossroad to surmount vital performance challenges. For more than four decades, the performance of general purpose computing systems has been improving by 20-50% per year [1]. In the last decade, this number has dropped to less than 7% per year. Most recently, that rate has slowed to only 3% per year. [1]. The demand for performance improvement, however, keeps increasing and diversifies within new application domains. This higher performance, however, often has to come at a lower power consumption cost too, adding to the complexity of the task of architectural design space optimization. Both today's computer architectures and device technologies (used to manufacture them) are facing major challenges to achieve the performance demands required by complex applications such as Artificial Intelligence (AI). The complexity stems from the extremely high number of operations to be computed and the involved amount of data. |
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| Item Description: | Gesehen am 14.10.2024 |
| Physical Description: | Online Resource |
| ISSN: | 2168-6750 |
| DOI: | 10.1109/TETC.2024.3369288 |