64 citations · 184 across the 14 of their papers we have counts for
16 papers
VortexSynth: Profile-guided benchmark reconstruction for GPU architecture research
Huanzhi Pu, Chulhyung Park, Chihyo Ahn +2
GPU architecture research requires representative benchmarks that can execute on new designs. However, many vendor-tailored workloads and library kernels cannot run directly on res…
Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference
Donghyeon Joo, Helya Hosseini, Ramyad Hadidi +1
We demonstrate that unstructured sparsity significantly improves KV cache compression for LLMs, enabling sparsity levels up to 70% without compromising accuracy or requiring fine-t…
Endor: Hardware-Friendly Sparse Format for Offloaded LLM Inference
Donghyeon Joo, Ramyad Hadidi, Soheil Feizi +1
The increasing size of large language models (LLMs) challenges their usage on resource-constrained platforms. For example, memory on modern GPUs is insufficient to hold LLMs that a…
Network architecture search of X-ray based scientific applications
Adarsha Balaji, Ramyad Hadidi, Gregory Kollmer +2
X-ray and electron diffraction-based microscopy use bragg peak detection and ptychography to perform 3-D imaging at an atomic resolution. Typically, these techniques are implemente…
Context-Aware Task Handling in Resource-Constrained Robots with Virtualization
Ramyad Hadidi, Nima Shoghi Ghalehshahi, Bahar Asgari +1
Intelligent mobile robots are critical in several scenarios. However, as their computational resources are limited, mobile robots struggle to handle several tasks concurrently and…
Creating Robust Deep Neural Networks With Coded Distributed Computing for IoT Systems
Ramyad Hadidi, Jiashen Cao, Hyesoon Kim
The increasing interest in serverless computation and ubiquitous wireless networks has led to numerous connected devices in our surroundings. Among such devices, IoT devices have a…
THIA: Accelerating Video Analytics using Early Inference and Fine-Grained Query Planning
Jiashen Cao, Ramyad Hadidi, Joy Arulraj +1
To efficiently process visual data at scale, researchers have proposed two techniques for lowering the computational overhead associated with the underlying deep learning models. T…
Secure Location-Aware Authentication and Communication for Intelligent Transportation Systems
Nima Shoghi Ghalehshahi, Ramyad Hadidi, Lee Jaewon +6
Intelligent transportation systems (ITS) are expected to effectively create a stand-alone network for secure communication among autonomous agents. In such a dynamic and fast-chang…
Reducing Inference Latency with Concurrent Architectures for Image Recognition
Ramyad Hadidi, Jiashen Cao, Michael S. Ryoo +1
Satisfying the high computation demand of modern deep learning architectures is challenging for achieving low inference latency. The current approaches in decreasing latency only i…
Copernicus: Characterizing the Performance Implications of Compression Formats Used in Sparse Workloads
Bahar Asgari, Ramyad Hadidi, Joshua Dierberger +3
Sparse matrices are the key ingredients of several application domains, from scientific computation to machine learning. The primary challenge with sparse matrices has been efficie…
LCP: A Low-Communication Parallelization Method for Fast Neural Network Inference in Image Recognition
Ramyad Hadidi, Bahar Asgari, Jiashen Cao +6
Deep neural networks (DNNs) have inspired new studies in myriad edge applications with robots, autonomous agents, and Internet-of-things (IoT) devices. However, performing inferenc…
Collaborative Execution of Deep Neural Networks on Internet of Things Devices
Ramyad Hadidi, Jiashen Cao, Micheal S. Ryoo +1
With recent advancements in deep neural networks (DNNs), we are able to solve traditionally challenging problems. Since DNNs are compute intensive, consumers, to deploy a service,…
Musical Chair: Efficient Real-Time Recognition Using Collaborative IoT Devices
Ramyad Hadidi, Jiashen Cao, Matthew Woodward +2
The prevalence of Internet of things (IoT) devices and abundance of sensor data has created an increase in real-time data processing such as recognition of speech, image, and video…
CODA: Enabling Co-location of Computation and Data for Near-Data Processing
Hyojong Kim, Ramyad Hadidi, Lifeng Nai +5
Recent studies have demonstrated that near-data processing (NDP) is an effective technique for improving performance and energy efficiency of data-intensive workloads. However, lev…
Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube
Ramyad Hadidi, Bahar Asgari, Jeffrey Young +4
Memories that exploit three-dimensional (3D)-stacking technology, which integrate memory and logic dies in a single stack, are becoming popular. These memories, such as Hybrid Memo…
Demystifying the Characteristics of 3D-Stacked Memories: A Case Study for Hybrid Memory Cube
Ramyad Hadidi, Bahar Asgari, Burhan Ahmad Mudassar +3
Three-dimensional (3D)-stacking technology, which enables the integration of DRAM and logic dies, offers high bandwidth and low energy consumption. This technology also empowers ne…