Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
CHARM: C omposing H eterogeneous A ccele R ators for M atrix Multiply on Versal ACAP Architecture
Dense matrix multiply (MM) serves as one of the most heavily used kernels in deep learning
applications. To cope with the high computation demands of these applications …
applications. To cope with the high computation demands of these applications …
Google neural network models for edge devices: Analyzing and mitigating machine learning inference bottlenecks
Emerging edge computing platforms often contain machine learning (ML) accelerators that
can accelerate inference for a wide range of neural network (NN) models. These models are …
can accelerate inference for a wide range of neural network (NN) models. These models are …
Highlight: Efficient and flexible dnn acceleration with hierarchical structured sparsity
Due to complex interactions among various deep neural network (DNN) optimization
techniques, modern DNNs can have weights and activations that are dense or sparse with …
techniques, modern DNNs can have weights and activations that are dense or sparse with …
An architecture-level analysis on deep learning models for low-impact computations
Deep neural networks (DNNs) have made significant achievements in a wide variety of
domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient …
domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient …
Creating the future: Augmented reality, the next human-machine interface
M Abrash - 2021 IEEE International Electron Devices Meeting …, 2021 - ieeexplore.ieee.org
XR, consisting of Virtual Reality (VR) and Augmented Reality (AR) together, will be the next
general computing platform, dominating our relationship with the digital world for the next 50 …
general computing platform, dominating our relationship with the digital world for the next 50 …
Moca: Memory-centric, adaptive execution for multi-tenant deep neural networks
Driven by the wide adoption of deep neural networks (DNNs) across different application
domains, multi-tenancy execution, where multiple DNNs are deployed simultaneously on …
domains, multi-tenancy execution, where multiple DNNs are deployed simultaneously on …
SSR: Spatial sequential hybrid architecture for latency throughput tradeoff in transformer acceleration
With the increase in the computation intensity of the chip, the mismatch between
computation layer shapes and the available computation resource significantly limits the …
computation layer shapes and the available computation resource significantly limits the …
Reconfigurability, why it matters in AI tasks processing: A survey of reconfigurable AI chips
Nowadays, artificial intelligence (AI) technologies, especially deep neural networks (DNNs),
play an vital role in solving many problems in both academia and industry. In order to …
play an vital role in solving many problems in both academia and industry. In order to …
Xrbench: An extended reality (xr) machine learning benchmark suite for the metaverse
Real-time multi-task multi-model (MTMM) workloads, a new form of deep learning inference
workloads, are emerging for applications areas like extended reality (XR) to support …
workloads, are emerging for applications areas like extended reality (XR) to support …
BitWave: Exploiting column-based bit-level sparsity for deep learning acceleration
Bit-serial computation facilitates bit-wise sequential data processing, offering numerous
benefits, such as a reduced area footprint and dynamically-adaptive computational …
benefits, such as a reduced area footprint and dynamically-adaptive computational …