activity
20182023
most citedSMASH: Co-designing Software Compression and Hardware-Accelerated Indexing for Efficient Sparse Matrix Operations

81 citations · 176 across the 12 of their papers we have counts for

collaborators

18 papers

cs.CR2023

An Experimental Analysis of RowHammer in HBM2 DRAM Chips

Ataberk Olgun, Majd Osseiran, Abdullah Giray Ya{ğ}lık{c}ı +6

RowHammer (RH) is a significant and worsening security, safety, and reliability issue of modern DRAM chips that can be exploited to break memory isolation. Therefore, it is importa…

q-bio.GN2022

Going From Molecules to Genomic Variations to Scientific Discovery: Intelligent Algorithms and Architectures for Intelligent Genome Analysis

Mohammed Alser, Joel Lindegger, Can Firtina +5

We now need more than ever to make genome analysis more intelligent. We need to read, analyze, and interpret our genomes not only quickly, but also accurately and efficiently enoug…

cs.AR20222 cited

High-throughput Pairwise Alignment with the Wavefront Algorithm using Processing-in-Memory

Safaa Diab, Amir Nassereldine, Mohammed Alser +3

We show that the wavefront algorithm can achieve higher pairwise read alignment throughput on a UPMEM PIM system than on a server-grade multi-threaded CPU system.

cs.LG20221 cited

EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators

Lois Orosa, Skanda Koppula, Yaman Umuroglu +5

Dilated and transposed convolutions are widely used in modern convolutional neural networks (CNNs). These kernels are used extensively during CNN training and inference of applicat…

cs.DC2022

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Mhd Ghaith Olabi, Juan Gómez Luna, Onur Mutlu +2

Dynamic parallelism on GPUs allows GPU threads to dynamically launch other GPU threads. It is useful in applications with nested parallelism, particularly where the amount of neste…

cs.AR202174 cited

FPGA-Based Near-Memory Acceleration of Modern Data-Intensive Applications

Gagandeep Singh, Mohammed Alser, Damla Senol Cali +4

Modern data-intensive applications demand high computation capabilities with strict power constraints. Unfortunately, such applications suffer from a significant waste of both exec…