Publication
Overflow-free compute memories for edge AI acceleration
Publications associées (48)
Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications
Joshua Alexander Harrison Klein
The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...
EPFL2024Towards General-Purpose Decentralized Computing with Permissionless Extensibility
Smart contracts have emerged as the most promising foundations for applications of the blockchain technology. Even though smart contracts are expected to serve as the backbone of the next-generation web, they have several limitations that hinder their wide ...
EPFL20242D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing
Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...
EPFL2023A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication
David Atienza Alonso, Giovanni Ansaloni, Grégoire Axel Eggermann, Marco Antonio Rios
State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...
2023Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference
David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, Flavio Ponzina
By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...
2023Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics
Anastasia Ailamaki, Viktor Sanca
Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...
2023HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics
Anastasia Ailamaki, Periklis Chrysogelos, Hamish Mcniece Hill Nicholson, Syed Mohammad Aunn Raza
Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...
2023Energy Efficient Logic and Memory Design With Beyond-CMOS Magnetoelectric Spin-Orbit (MESO) Technology Toward Ultralow Supply Voltage
Devices based on the spin as the fundamental computing unit provide a promising beyond-complementary metal-oxide-semiconductor (CMOS) device option, thanks to their energy efficiency and compatibility with CMOS. One such option is a magnetoelectric spin-or ...
Piscataway2023Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2
Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Zhenyu Wang, Guilherme Migliato Marega
Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...
2022The Lang-Trotter conjecture for products of non-CM elliptic curves
Inspired by the work of Lang-Trotter on the densities of primes with fixed Frobenius traces for elliptic curves defined over Q and by the subsequent generalization of Cojocaru-Davis-Silverberg-Stange to generic abelian varieties, we study the analogous que ...
SPRINGER2022