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WPC: Whole-Picture Workload Characterization Across Intermediate Representation, ISA, and Microarchitecture

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2021; 20 (2)

This letter reveals that performing microarchitecture-dependent, or microarchitecture-independent, or ISA-independent workload characterization alone ......

Hardware Acceleration for GCNs via Bidirectional Fusion

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2021; 20 (1)

Derived from the fusion of graph traversal and neural networks, graph convolutional neural networks (GCNs) have achieved state-of-the-art performance ......

Dagger: Towards Efficient RPCs in Cloud Microservices With Near-Memory Reconfigurable NICs

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2020; 19 (2)

Cloud applications are increasingly relying on hundreds of loosely-coupled microservices to complete user requests that meet an application's end-to-e......

Characterizing and Understanding GCNs on GPU

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2020; 19 (1)

Graph convolutional neural networks (GCNs) have achieved state-of-the-art performance on graph-structured data analysis. Like traditional neural netwo......

A High-Performance Design of Generalized Pipeline Cellular Array

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2020; 19 (1)

In this letter, we proposed a high-performance quantum-dot cellular automata (QCA) design of generalized pipeline cellular array (GPCA). The GPCA can ......

Architectural Implications of Graph Neural Networks

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2020; 19 (1)

Graph neural networks (GNN) represent an emerging line of deep learning models that operate on graph structures. It is becoming more and more popular ......

PIMSim: A Flexible and Detailed Processing-in-Memory Simulator

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (1)

With the advent of big data applications and new process technologies, Process-in-Memory (PIM) attracts much attention in memory research as the archi......

JIF:1.15

SVSoC: Speculative Vision Systems-on-a-Chip

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (1)

Frame latency in continuous vision significantly impacts the agility of intelligent machines that interact with the environment via cameras. However, ......

JIF:1.15

A Unified Framework for Training, Mapping and Simulation of ReRAM-Based Convolutional Neural Network Acceleration

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (1)

ReRAM-based neural network accelerators (RNAs) could outshine their digital counterparts in terms of computational efficiency and performance remarkab......

JIF:1.15

Asymmetric Resilience for Accelerator-Rich Systems

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (1)

Accelerators are becoming popular owing to their exceptional performance and power-efficiency. However, researchers are yet to pay close attention to ......

JIF:1.15

ARCE: Towards Code Pointer Integrity on Embedded Processors Using Architecture-Assisted Run-Time Metadata Management

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (2)

Code Pointer Integrity (CPI) is an efficient control flow protection technique focusing on sensitive code pointers with a formal proof of security, bu......

JIF:1.15

Priority-Based PCIe Scheduling for Multi-Tenant Multi-GPU Systems

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2019; 18 (2)

Multi-GPU systems are widely used in data centers to provide significant speedups to compute-intensive workloads such as deep neural network training.......

JIF:1.15

KSM: Online Application-Level Performance Slowdown Prediction for Spatial Multitasking GPGPU

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2018; 17 (2)

Colocating multiple applications on the same spatial multitasking GPGPU improves the system-wide throughput. However, the colocated applications are s......

JIF:1.15

RETROFIT: Fault-Aware Wear Leveling

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2018; 17 (2)

Phase-change memory (PCM) and resistive memory (RRAM) are promising alternatives to traditional memory technologies. However, both PCM and RRAM suffer......

JIF:1.15

Vertical Writes: Closing the Throughput Gap between Deeply Scaled STT-MRAM and DRAM

期刊: IEEE COMPUTER ARCHITECTURE LETTERS, 2018; 17 (2)

STT-MRAMis a second generation MRAM technology that addresses many of the scaling problems of earlier generation magnetic RAMs, and is a promising can......

JIF:1.15

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