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Domain-specific neural network accelerators have seen growing interest in recent years due to their improved energy efficiency and inference performance compared to CPUs and GPUs. In this paper, we propose a novel cross-layer optimized…
Energy harvesting is a promising solution to power Internet of Things (IoT) devices. Due to the intermittent nature of these energy sources, one cannot guarantee forward progress of program execution. Prior work has advocated for…
Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms, and it is used as a proof-of-work function in several cryptocurrencies. The most crucial and exotic hashing algorithm in the Lyra2REv2 chain is a…
Deep learning algorithms are a key component of many state-of-the-art vision systems, especially as Convolutional Neural Networks (CNN) outperform most solutions in the sense of accuracy. To apply such algorithms in real-time applications,…
Visual information processing will play an increasingly important role in future electronics systems. In many applications, e.g. video surveillance cameras, data throughput of microprocessors is not sufficient and power consumption is too…
We argue that the current POW based consensus algorithm of the Bitcoin network suffers from a fundamental economic discrepancy between the real world transaction (txn) costs incurred by miners and the wealth that is being transacted. Put…
The widespread adoption of cloud-based solutions introduces privacy and security concerns. Techniques such as homomorphic encryption (HE) mitigate this problem by allowing computation over encrypted data without the need for decryption.…
In-browser cryptojacking involves hijacking the CPU power of a website's visitor to perform CPU-intensive cryptocurrency mining, and has been on the rise, with 8500% growth during 2017. While some websites advocate cryptojacking as a…
Permissionless blockchains such as Bitcoin have long been criticized for their high computational and storage overhead. Unfortunately, while a number of proposals address the energy consumption of existing Proof-of-Work deployments, little…
In recent years, processing in memory (PIM) based mixedsignal designs have been proposed as energy- and area-efficient solutions with ultra high throughput to accelerate DNN computations. However, PIM designs are sensitive to imperfections…
With the increasing artificial intelligence application, deep neural network (DNN) has become an emerging task. However, to train a good deep learning model will suffer from enormous computation cost and energy consumption. Recently,…
Cryptographic operations are an essential component of cloud security architectures; their comprehensive performance characterization across different cloud services, hardware architectures, and programming language implementations remains…
A soft control of the network activity through varying reward in a proof-of-work (PoW) cryptocurrency is reported. Rewards are the necessity to incent the contributors activities (i.e., mining) in order to maintain the PoW network. Contrary…
Automatic code generation is frequently used to create implementations of algorithms specifically tuned to particular hardware and application parameters. The code generation process involves the selection of adequate code transformations,…
Lattice-based cryptographic algorithms built on ring learning with error theory are gaining importance due to their potential for providing post-quantum security. However, these algorithms involve complex polynomial operations, such as…
In this paper, we developed an Electromagnetic Transient (EMT) model tailored for large cryptocurrency mining loads to understand the cross-interaction of these loads with the electric grid. The load model has been built using…
Whilst the RISC-V Vector extension (RVV) has been ratified, at the time of writing both hardware implementations and open source software support are still limited for vectorisation on RISC-V. This is important because vectorisation is…
Specialized image processing accelerators are necessary to deliver the performance and energy efficiency required by important applications in computer vision, computational photography, and augmented reality. But creating,…
The power consumption of a microprocessor is a huge channel for information leakage. While the most popular exploitation of this channel is to recover cryptographic keys from embedded devices, other applications such as mobile app…
Recently, large language models (LLMs) have achieved huge success in the natural language processing (NLP) field, driving a growing demand to extend their deployment from the cloud to edge devices. However, deploying LLMs on…