4 citations · 5 across the 23 of their papers we have counts for
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High-Performance NTT Accelerators for PQC leveraging Unified Redundant Arithmetic and Fine-Tuned Microarchitecture
George Alexakis, Dimitrios Schoinianakis, Giorgos Dimitrakopoulos
Post-quantum cryptography and privacy-preserving technologies are expected to play a central role in future secure communication systems. Lattice-based PQC schemes such as ML-KEM (…
MIVE: A Minimalist Integer Vector Engine for Softmax LayerNorm and RMSNorm Acceleration
Kosmas Alexandridis, Giorgos Dimitrakopoulos
The rapid growth of Large Language Models (LLMs) has intensified the need for specialized hardware accelerators that can satisfy stringent inference latency and power constraints.…
H-FA: A Hybrid Floating-Point and Logarithmic Approach to Hardware Accelerated FlashAttention
Kosmas Alexandridis, Giorgos Dimitrakopoulos
Transformers have significantly advanced AI and machine learning through their powerful attention mechanism. However, computing attention on long sequences can become a computation…
High-Performance Pipelined NTT Accelerators with Homogeneous Digit-Serial Modulo Arithmetic
George Alexakis, Dimitrios Schoinianakis, Giorgos Dimitrakopoulos
The Number Theoretic Transform (NTT) is a fundamental operation in privacy-preserving technologies, particularly within fully homomorphic encryption (FHE). The efficiency of NTT co…
Low-Cost FlashAttention with Fused Exponential and Multiplication Hardware Operators
Kosmas Alexandridis, Vasileios Titopoulos, Giorgos Dimitrakopoulos
Attention mechanisms, particularly within Transformer architectures and large language models (LLMs), have revolutionized sequence modeling in machine learning and artificial intel…
Efficient Implementation of RISC-V Vector Permutation Instructions
Vasileios Titopoulos, George Alexakis, Chrysostomos Nicopoulos +1
RISC-V CPUs leverage the RVV (RISC-V Vector) extension to accelerate data-parallel workloads. In addition to arithmetic operations, RVV includes powerful permutation instructions t…