1 citations · 1 across the 8 of their papers we have counts for
9 papers
CALIPER: Calibrating HPC/AI Network Simulators
Seyyidahmed Lahmer, Daniel Seibel, Srijeet Basu +9
Network simulation plays an important role in HPC/AI system research by enabling exploration of network architectures, communication strategies, and system configurations at scales…
Evaluating Cross-Architecture Performance Modeling of Distributed ML Workloads Using StableHLO
Jonas Svedas, Nathan Laubeuf, Ryan Harvey +6
Predicting the performance of large-scale distributed machine learning (ML) workloads across multiple accelerator architectures remains a central challenge in ML system design. Exi…
Decoupled Control Flow and Data Access in RISC-V GPGPUs
Giuseppe M. Sarda, Nimish Shah, Abubakr Nada +2
Vortex, a newly proposed open-source GPGPU platform based on the RISC-V ISA, offers a valid alternative for GPGPU research over the broadly-used modeling platforms based on commerc…
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO
Jonas Svedas, Hannah Watson, Nathan Laubeuf +6
Distributed deep neural networks (DNNs) have become a cornerstone for scaling machine learning to meet the demands of increasingly complex applications. However, the rapid growth i…
Addressing memory bandwidth scalability in vector processors for streaming applications
Jordi Altayo, Paul Delestrac, David Novo +3
As the size of artificial intelligence and machine learning (AI/ML) models and datasets grows, the memory bandwidth becomes a critical bottleneck. The paper presents a novel extend…
A System Level Performance Evaluation for Superconducting Digital Systems
Joyjit Kundu, Debjyoti Bhattacharjee, Nathan Josephsen +8
Superconducting Digital (SCD) technology offers significant potential for enhancing the performance of next generation large scale compute workloads. By leveraging advanced lithogr…
SAfEPaTh: A System-Level Approach for Efficient Power and Thermal Estimation of Convolutional Neural Network Accelerator
Yukai Chen, Simei Yang, Debjyoti Bhattacharjee +2
The design of energy-efficient, high-performance, and reliable Convolutional Neural Network (CNN) accelerators involves significant challenges due to complex power and thermal mana…
Optimising GPGPU Execution Through Runtime Micro-Architecture Parameter Analysis
Giuseppe M. Sarda, Nimish Shah, Debjyoti Bhattacharjee +2
GPGPU execution analysis has always been tied to closed-source, proprietary benchmarking tools that provide high-level, non-exhaustive, and/or statistical information, preventing a…
Full-stack evaluation of Machine Learning inference workloads for RISC-V systems
Debjyoti Bhattacharjee, Anmol, Tommaso Marinelli +2
Architectural simulators hold a vital role in RISC-V research, providing a crucial platform for workload evaluation without the need for costly physical prototypes. They serve as a…