Related papers: BRAVO -- Biased Locking for Reader-Writer Locks

The success of neural networks comes hand in hand with a desire for more interpretability. We focus on text classifiers and make them more interpretable by having them provide a justification, a rationale, for their predictions. We approach…

In-memory computing is becoming a popular architecture for deep-learning hardware accelerators recently due to its highly parallel computing, low power, and low area cost. However, in-RRAM computing (IRC) suffered from large device…

Hotspots, a small set of tuples frequently read/written by a large number of transactions, cause contention in a concurrency control protocol. While a hotspot may comprise only a small fraction of a transaction's execution time,…

Designing protocols and formulating convenient programming units of abstraction for sensor networks is challenging due to communication errors and platform constraints. This paper investigates properties and implementation reliability for a…

Computing-in-Memory architectures based on non-volatile emerging memories have demonstrated great potential for deep neural network (DNN) acceleration thanks to their high energy efficiency. However, these emerging devices can suffer from…

Collaborative filtering is one of the most common scenarios and popular research topics in recommender systems. Among existing methods, latent factor models, i.e., learning a specific embedding for each user/item by reconstructing the…

Concept Factorization (CF) and its variants may produce inaccurate representation and clustering results due to the sensitivity to noise, hard constraint on the reconstruction error and pre-obtained approximate similarities. To improve the…

Reinforcement learning (RL) has emerged as a critical technique for enhancing LLM-based deep search agents. However, existing approaches primarily rely on binary outcome rewards, which fail to capture the comprehensiveness and factuality of…

Transformer-based models have demonstrated superior performance in various fields, including natural language processing and computer vision. However, their enormous model size and high demands in computation, memory, and communication…

In this paper, we describe a general framework: Parameters Read-Write Networks (PRaWNs) to systematically analyze current neural models for multi-task learning, in which we find that existing models expect to disentangle features into…

Data is replicated and stored redundantly over multiple servers for availability in distributed databases. We focus on databases with frequent reads and writes, where both read and write latencies are important. This is in contrast to…

We introduce LITcoder, an open-source library for building and benchmarking neural encoding models. Designed as a flexible backend, LITcoder provides standardized tools for aligning continuous stimuli (e.g., text and speech) with brain…

Large language models (LLMs) have shown great success in various Natural Language Processing (NLP) tasks, whist they still need updates after deployment to fix errors or keep pace with the changing knowledge in the world. Researchers…

Algebraic Manipulation Detection (AMD) Codes detect adversarial noise that is added to a coded message and stored in a storage that is opaque to the adversary. We study AMD codes when the storage can leak up to \rho\log|G| bits of…

Due to low power consumption and high-speed performance, superconductor circuit technology has emerged as an attractive and compelling post-CMOS technology candidate. However, the design of dense memory circuits presents a significant…

This paper proposes a novel hybrid-domain (HD) non-orthogonal multiple access (NOMA) approach to support a larger number of uplink users than the recently proposed code-domain NOMA approach, i.e., sparse code multiple access (SCMA). HD-NOMA…

Auditability allows to track operations performed on a shared object, recording who accessed which information. This gives data owners more control on their data. Initially studied in the context of single-writer registers, this work…

It is becoming increasingly difficult to improve the performance of a a single process (thread) on a computer due to physical limitations. Modern systems use multi-core processors in which multiple processes (threads) may run concurrently.…

FIFO queues with a single reader and writer can be insufficient for "hard real-time" systems where interrupt handlers require wait-free guarantees when writing to message queues. We present an algorithm which elegantly and practically…

The pivotal storage density win achieved by solid-state devices over magnetic devices recently is a result of multiple innovations in physics, architecture, and signal processing. Constrained coding is used in Flash devices to increase…