Area of research
Computer Networks and Communications · Hardware and Architecture
Research interest
Research interests include Parallel Computing and Optimization Techniques, Advanced Data Storage Technologies, Distributed and Parallel Computing Systems, and Interconnection Networks and Systems.
Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware.
GPU Acceleration of Sparse Fully Homomorphic Encrypted DNNs
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training
Scalability Limitations of Processing-in-Memory using Real System Evaluations
Scalability Limitations of Processing-in-Memory using Real System Evaluations
Scalability Limitations of Processing-in-Memory using Real System Evaluations
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption
Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs
Thought Bubbles: A Proxy into Players’ Mental Model Development
Characterizing and Exploiting Soft Error Vulnerability Phase Behavior in GPU Applications
VCSR: An Efficient GPU Memory-Aware Sparse Format
Framework for Denoising Monte Carlo Photon Transport Simulations Using Deep Learning
Daisen: A Framework for Visualizing Detailed GPU Execution
Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs
Analyzing and Increasing the Reliability of Convolutional Neural Networks on GPUs
Priority-Based PCIe Scheduling for Multi-Tenant Multi-GPU Systems
Intra-Cluster Coalescing and Distributed-Block Scheduling to Reduce GPU NoC Pressure
Student cluster competition 2018, team northeastern university: Reproducing performance of a multi-physics simulations of the Tsunamigenic 2004 Sumatra Megathrust earthquake on the AMD EPYC 7551 architecture
Profiling DNN Workloads on a Volta-based DGX-1 System
Mystic: Predictive Scheduling for GPU Based Cloud Servers Using Machine Learning
Asymmetric NoC Architectures for GPU Systems
Collaborative Research: CSR: Medium: Architecting GPUs for Practical Homomorphic Encryption-based Computing
MRI: Acquisition of a Heterogeneous Multi-GPU Cluster to Support Exploration at Scale
REU Site: REU Research Experiences and Mentoring in Data-Driven Discovery
STARSS: Small: Side-Channel Analysis and Resiliency Targeting Accelerators
Northeastern University Planning Grant: I/UCRC for Energy-Smart Electronic Systems
Student Travel for PACT 2016
CSR: Small: Collaborative Research: Leveraging Intra-chip/Inter-chip Silicon-Photonic Networks for Designing Next-Generation Accelerators
SHF: Small: The Cross-layer Reliability Stack
Support for the 37th International Symposium on Computer Architecture (ISCA 2010)
A Biomedical Imaging Acceleration Testbed
CRI: CRD Collaborative Research: Archer - Seeding a Community-based Computing Infrastructure for Computer Architecture Research and Education
Collaborative Research: Tuning Libraries to Effectively Exploit the Memory Hierarchy
Architectural Support for Virus Detection and Recovery
CISE Research Instrumentation: Development of a Digital Signal Processing (DSP) Compilation Testbed
CAREER: Architectural Support for Object-oriented Code Execution