activity
20222026
most citedLeveraging Apache Arrow for Zero-copy, Zero-serialization Cluster Shared Memory

1 citations · 2 across the 9 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Misalignment of Low-Loss Regions Causes Grokking

Yongding Tian, Zaid Al-Ars, Maksim Kitsak +1

Grokking refers to the delayed emergence of validation-set generalization after a model has already overfit the training set. Although first observed in small algorithmic tasks tra…

cs.LG2025

Connecting Independently Trained Modes via Layer-Wise Connectivity

Yongding Tian, Zaid Al-Ars, Maksim Kitsak +1

Empirical studies have shown that continuous low-loss paths can be constructed between independently trained neural network models. This phenomenon, known as mode connectivity, ref…

cs.PF2024

TINA: Acceleration of Non-NN Signal Processing Algorithms Using NN Accelerators

Christiaan Boerkamp, Steven van der Vlugt, Zaid Al-Ars

This paper introduces TINA, a novel framework for implementing non Neural Network (NN) signal processing algorithms on NN accelerators such as GPUs, TPUs or FPGAs. The key to this…

cs.AR2024

Tywaves: A Typed Waveform Viewer for Chisel

Raffaele Meloni, H. Peter Hofstee, Zaid Al-Ars

Chisel (Constructing Hardware In a Scala Embedded Language) is a broadly adopted HDL that brings object-oriented and functional programming, type-safety, and parameterization to ha…

cs.ET2024★ 1 cited

Leveraging Apache Arrow for Zero-copy, Zero-serialization Cluster Shared Memory

Philip Groet, Joost Hoozemans, Andreas Grapentin +3

This paper describes a distributed implementation of Apache Arrow that can leverage cluster-shared load-store addressable memory that is hardware-coherent only within each node. Th…

cs.LG2024

Vanishing Variance Problem in Fully Decentralized Neural-Network Systems

Yongding Tian, Zaid Al-Ars, Maksim Kitsak +1

Federated learning and gossip learning are emerging methodologies designed to mitigate data privacy concerns by retaining training data on client devices and exclusively sharing lo…

cs.LG2024

NASH: Neural Architecture Search for Hardware-Optimized Machine Learning Models

Mengfei Ji, Yuchun Chang, Baolin Zhang +1

As machine learning (ML) algorithms get deployed in an ever-increasing number of applications, these algorithms need to achieve better trade-offs between high accuracy, high throug…

cs.LG2024

NLICE: Synthetic Medical Record Generation for Effective Primary Healthcare Differential Diagnosis

Zaid Al-Ars, Obinna Agba, Zhuoran Guo +3

This paper offers a systematic method for creating medical knowledge-grounded patient records for use in activities involving differential diagnosis. Additionally, an assessment of…

cs.PL2023

An Intermediate Representation for Composable Typed Streaming Dataflow Designs

Matthijs A. Reukers, Yongding Tian, Zaid Al-Ars +4

Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred ov…

cs.PL2022★ 1 cited

Tydi-lang: a language for typed streaming hardware -- A manual for future Tydi-lang compiler developers

Yongding Tian, Zaid Al-Ars, Peter Hofstee

Transferring composite data structures with variable-length fields often requires designing non-trivial protocols that are not compatible between hardware designs. When each projec…