IEEE

A Sparse Deep Neural Network Inference Accelerator

Abstract: This paper proposes a sparse Deep Neural Network (DNN) inference accelerator architecture that can be used for a reconfigurable edge computing platform that improves computational efficiency ...
IEEE

MotifGT-DTI: Pivotal Motif-Based Graph Transformer Model Improves Drug–Target Interaction Prediction

Abstract: Predicting drug–target interactions (DTIs) plays an essential role in drug discovery and drug repurposing. Although significant performance improvements have been achieved in DTI prediction, ...
IEEE

A Trust Model for Human-Machine Interaction in Virtual Reality

Abstract: Human trust in machines is critical for effective human-machine interaction in virtual reality (VR). Prior work defined a three-layered framework of such trust but also indicated two ...
IEEE

An Adaptive Feature Interaction Learning Model for QoS Prediction With Multi-Source Context

Abstract: The increasingly dynamic and diversified cloud service network environment poses many challenges to the QoS prediction in the field of service recommendation. How to predict the quality of ...
IEEE

Benchmarking AI Inference Efficiency in Public and Private Clouds: an MLPerf-Based Comparative Study

Abstract: AI inference is emerging as a major driver of energy consumption in large-scale computing environments, yet most existing research focuses on the training phase of machine learning models.
IEEE

Exploiting Output Activation Sparsity Using Bit-Separable Multiplier in CNN Accelerator

Abstract: This paper demonstrates a bit-separable multiplier (BSM) in CNN accelerators to leverage output activation sparsity. BSM improves computational efficiency by predicting the output of ...
IEEE

System-level performance analysis for CNN model deployment using CPU, GPU and AI Accelerator

Abstract: Deploying Convolutional Neural Networks (CNNs) efficiently across heterogeneous hardware platforms—such as CPUs, GPUs, and dedicated AI accelerators—remains a significant challenge due to ...
IEEE

Enabling Decoder-only Language Model Inference on a CNN Accelerator

Abstract: The remarkable success of Transformer architectures in Natural Language Processing (NLP) has led to increased demand for embedded systems capable of efficiently handling NLP tasks along with ...
IEEE

ParaPM: Efficient Hardware Accelerator for Postquantum Signature With High-Performance Polynomial Multiplier

Abstract: During the Institute of Standards and Technology (NIST) postquantum cryptography standardization process, the lattice-based Dilithium scheme was selected as one of the three third-round ...
Morningstar

Broadcom's stock picks up a rare downgrade. What's behind the contrarian call.

An analyst worries about a line from a recent Broadcom filing that suggests the company may be somewhat involved in the funding of an Anthropic data center Broadcom's stock has more than doubled over ...
IEEE

Hardware-Model Co-Optimization of Compressed Neural Network Accelerator for Real-Time Compensation in Precision Motion Control

Abstract: For precision motion control systems, real-time feedforward compensation is indispensable, yet its implementation is constrained by latency, computational/storage hardware resources. Classic ...
Ars Technica

From folding boxes to fixing vacuums, GEN-1 robotics model hits 99% reliability

Robotic machine-learning company Generalist has announced GEN-1, a new physical AI system that it says “crosses into production-level success rates” on “a broad range of physical skills” that used to ...