Publications

Situla: Studying the Interplay of Sparse Formats and CPU/GPU Libraries

Amirmahdi Namjoo, Sanjali Yadav, Helya Hosseini, Bahar Asgari

IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) · 2026

A characterization of sparse-dense and sparse-sparse matrix multiplication across Intel Xeon CPUs, NVIDIA H100 GPUs, and Arm Neoverse processors, studying how sparse format, software library, matrix structure, performance, and energy interact.

Chasoń: Supporting Cross HBM Channel Data Migration to Enable Efficient Sparse Algebraic Acceleration

Ubaid Bakhtiar, Amirmahdi Namjoo, Bahar Asgari

58th IEEE/ACM International Symposium on Microarchitecture (MICRO) · 2025

An HBM-based streaming accelerator for sparse matrix-vector multiplication that migrates data across HBM channels (Cross-HBM Channel out-of-order scheduling) to mitigate resource underutilization.

Misam: Machine Learning Assisted Dataflow Selection in Accelerators for Sparse Matrix Multiplication

Sanjali Yadav, Amirmahdi Namjoo, Bahar Asgari

58th IEEE/ACM International Symposium on Microarchitecture (MICRO) · 2025

A machine-learning framework that uses a lightweight decision tree and FPGA reconfiguration to select the optimal dataflow for sparse matrix-matrix multiplication at runtime.

Novel Distance-Learning Methods to Overcome Challenges Caused by COVID-19 in Undergraduate Programming Courses

Amirmahdi Namjoo, Seyed Parsa Neshaei, Parham Chavoshian, Parham Saremi, Mohammad Taha Jahani-Nezhad, AmirMahdi Kousheshi, Mohammadamin Fazli

14th International Conference on Education and New Learning Technologies (EDULEARN) · 2022

Distance-learning techniques used to improve the education and assessment of undergraduate programming courses at Sharif University of Technology during the COVID-19 pandemic.