Ben Feinberg

Orcid: 0000-0002-0450-0067

According to our database1, Ben Feinberg authored at least 25 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Incorruptible Neural Networks: Training Models that can Generalize to Large Internal Perturbations.
CoRR, February, 2026

Let Analog Be Analog: Principles for Designing Analog Accelerators.
IEEE Micro, 2026

DARTH-PUM: A Hybrid Processing-Using-Memory Architecture.
Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

Noise-Agnostic One-Shot Training and Retraining for Robust DNN Inferencing on Analog Compute-in-Memory Systems.
Proceedings of the 31st Asia and South Pacific Design Automation Conference, 2026

2025
Simulating Hybrid Analog + RISC-V Systems for HPC Applications.
Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, 2025

Fault Tolerance in RRAM-based AI Accelerator with Guided Randomized Activation.
Proceedings of the IEEE International Test Conference, 2025

ANVIL: An In-Storage Accelerator for Name-Value Data Stores.
Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

2024
Analog fast Fourier transforms for scalable and efficient signal processing.
CoRR, 2024

TCAM-SSD: A Framework for Search-Based Computing in Solid-State Drives.
CoRR, 2024

SEFsim: A Statistically-Guided Fast DRAM Simulator.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2024

2023
Evaluation of HPC Workloads Running on Open-Source RISC-V Hardware.
Proceedings of the High Performance Computing, 2023

Evaluation of Autonomous Vehicle Sensing and Compute Load on a Chassis Dynamometer.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

ERAS: A Flexible and Scalable Framework for Seamless Integration of RTL Models with Structural Simulation Toolkit.
Proceedings of the IEEE International Symposium on Workload Characterization, 2023

2022
An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory.
IEEE Trans. Circuits Syst. I Regul. Pap., 2022

Eris: Fault Injection and Tracking Framework for Reliability Analysis of Open-Source Hardware.
Proceedings of the International IEEE Symposium on Performance Analysis of Systems and Software, 2022

ATHENA: Enabling Codesign for Next-Generation AI/ML Architectures.
Proceedings of the IEEE International Conference on Rebooting Computing, 2022

Analog Neural Network Inference Accuracy in One-Selector One-Resistor Memory Arrays.
Proceedings of the IEEE International Conference on Rebooting Computing, 2022

2021
On the Accuracy of Analog Neural Network Inference Accelerators.
CoRR, 2021

An Analog Preconditioner for Solving Linear Systems.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2021

2020
Adapting In Situ Accelerators for Sparsity with Granular Matrix Reordering.
IEEE Comput. Archit. Lett., 2020

Evaluating complexity and resilience trade-offs in emerging memory inference machines.
Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020

Commutative Data Reordering: A New Technique to Reduce Data Movement Energy on Sparse Inference Workloads.
Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Device-aware inference operations in SONOS nonvolatile memory arrays.
Proceedings of the 2020 IEEE International Reliability Physics Symposium, 2020

2018
Enabling Scientific Computing on Memristive Accelerators.
Proceedings of the 45th ACM/IEEE Annual International Symposium on Computer Architecture, 2018

Making Memristive Neural Network Accelerators Reliable.
Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2018


  Loading...