A Programmable Crypto-Processor for National Institute of Standards and Technology Post-Quantum Cryptography Standardization Based on the RISC-V Architecture. [PDF]
Lee J, Kim W, Kim JH.
europepmc +1 more source
A RISC-V vector processor with tightly-integrated switched-capacitor DC-DC converters in 28nm FDSOI [PDF]
Brian Zimmer +18 more
openalex +1 more source
Manticore: A 4096-Core RISC-V Chiplet Architecture for Ultraefficient Floating-Point Computing [PDF]
Florian Zaruba +2 more
openalex +1 more source
Quantum mechanical calculations demonstrate that Norrish Type I photoinitiators generate radicals in 3D laser printing through two‐photon absorption and bond cleavage in the lowest triplet state. In contrast, Type II photoinitiators initiate polymerization via processes involving higher triplet states and a unique third‐order mechanism.
Anna Mauri +3 more
wiley +1 more source
CRYPHTOR: A Memory-Unified NTT-Based Hardware Accelerator for Post-Quantum CRYSTALS Algorithms
This paper presents the design and FPGA implementation of a hardware accelerator for the Post-Quantum CRYSTALS-Kyber and CRYSTALS-Dilithium algorithms, named CRYPHTOR (CRYstals Polynomial HW acceleraTOR).
Stefano Di Matteo +2 more
doaj +1 more source
GRVI Phalanx: A Massively Parallel RISC-V FPGA Accelerator Accelerator [PDF]
Jan Gray
openalex +1 more source
Heterogeneous 3D Integration for a RISC-V System With STT-MRAM [PDF]
Lingjun Zhu +8 more
openalex +1 more source
A comparative survey of open-source application-class RISC-V processor implementations [PDF]
Alexander Dörflinger +8 more
openalex +1 more source
Enhanced Cuckoo Search for Model Order Reduction ABSTRACT This article presents a critical review of classical and modern pole clustering techniques for model order reduction in high‐order systems. It highlights key limitations and common pitfalls encountered in traditional approaches, especially when extended to Multi‐Input Multi‐Output (MIMO) systems.
Kamel Ben Slimane +2 more
wiley +1 more source
Spike-RISC: Algorithm/ISA Co-Optimization for Efficient SNNs on RISC-V
Artificial intelligence has proven its benefits in many domains. Yet, traditional deep learning models are still too energy and compute-intensive for resource-constrained edge environments.
Ipek Akdeniz +3 more
doaj +1 more source

