8 citations · 8 across the 2 of their papers we have counts for
6 papers
SpecPCM: A Low-power PCM-based In-Memory Computing Accelerator for Full-stack Mass Spectrometry Analysis
Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu +6
Mass spectrometry (MS) is essential for proteomics and metabolomics but faces impending challenges in efficiently processing the vast volumes of data. This paper introduces SpecPCM…
HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations
Derek Jones, Jonathan E. Allen, Xiaohua Zhang +5
Publicly available collections of drug-like molecules have grown to comprise 10s of billions of possibilities in recent history due to advances in chemical synthesis. Traditional m…
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
Gopi Krishna Jha, Anthony Thomas, Nilesh Jain +3
Deep learning-based recommendation systems (e.g., DLRMs) are widely used AI models to provide high-quality personalized recommendations. Training data used for modern recommendatio…
SurGBSA: Learning Representations From Molecular Dynamics Simulations
Derek Jones, Yue Yang, Felice C. Lightstone +3
Self-supervised pretraining from static structures of drug-like compounds and proteins enable powerful learned feature representations. Learned features demonstrate state of the ar…
HPVM-HDC: A Heterogeneous Programming System for Accelerating Hyperdimensional Computing
Russel Arbore, Xavier Routh, Abdul Rafae Noor +7
Hyperdimensional Computing (HDC), a technique inspired by cognitive models of computation, has been proposed as an efficient and robust alternative basis for machine learning. HDC…
Hybrid SLC-MLC RRAM Mixed-Signal Processing-in-Memory Architecture for Transformer Acceleration via Gradient Redistribution
Chang Eun Song, Priyansh Bhatnagar, Zihan Xia +3
Transformers, while revolutionary, face challenges due to their demanding computational cost and large data movement. To address this, we propose HyFlexPIM, a novel mixed-signal pr…