15 citations · 35 across the 27 of their papers we have counts for
10 papers · 1 filter
EdgeCIM: A Hardware-Software Co-Design for CIM-Based Acceleration of Small Language Models
Jinane Bazzi, Mariam Rakka, Fadi Kurdahi +2
The growing demand for deploying Small Language Models (SLMs) on edge devices, including laptops, smartphones, and embedded platforms, has exposed fundamental inefficiencies in exi…
SoftmAP: Software-Hardware Co-design for Integer-Only Softmax on Associative Processors
Mariam Rakka, Jinhao Li, Guohao Dai +3
Recent research efforts focus on reducing the computational and memory overheads of Large Language Models (LLMs) to make them feasible on resource-constrained devices. Despite adva…
BF-IMNA: A Bit Fluid In-Memory Neural Architecture for Neural Network Acceleration
Mariam Rakka, Rachid Karami, Ahmed M. Eltawil +2
Mixed-precision quantization works Neural Networks (NNs) are gaining traction for their efficient realization on the hardware leading to higher throughput and lower energy. In-Memo…
Towards Efficient IMC Accelerator Design Through Joint Hardware-Workload Co-optimization
Olga Krestinskaya, Mohammed E. Fouda, Ahmed Eltawil +1
Designing generalized in-memory computing (IMC) hardware that efficiently supports a variety of workloads requires extensive design space exploration, which is infeasible to perfor…
Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions
Kamilya Smagulova, Mohammed E. Fouda, Ahmed Eltawil
The higher speed, scalability and parallelism offered by ReRAM crossbar arrays foster development of ReRAM-based next generation AI accelerators. At the same time, sensitivity of R…
DNA Pattern Matching Acceleration with Analog Resistive CAM
Jinane Bazzi, Jana Sweidan, Mohammed E. Fouda +2
DNA pattern matching is essential for many widely used bioinformatics applications. Disease diagnosis is one of these applications, since analyzing changes in DNA sequences can inc…
DT2CAM: A Decision Tree to Content Addressable Memory Framework
Mariam Rakka, Mohammed E. Fouda, Rouwaida Kanj +1
Decision trees are considered one of the most powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications that have limite…
Efficient Analog CAM Design
Jinane Bazzi, Jana Sweidan, Mohammed E. Fouda +2
Content Addressable Memories (CAMs) are considered a key-enabler for in-memory computing (IMC). IMC shows order of magnitude improvement in energy efficiency and throughput compare…
In-memory Multi-valued Associative Processor
Mira Hout, Mohammed E. Fouda, Rouwaida Kanj +1
In-memory associative processor architectures are offered as a great candidate to overcome memory-wall bottleneck and to enable vector/parallel arithmetic operations. In this paper…
Resistive Neural Hardware Accelerators
Kamilya Smagulova, Mohammed E. Fouda, Fadi Kurdahi +2
Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in real-time. However, their…