Related papers: Modularising Verification Of Durable Opacity

Deep neural networks for computer vision are deployed in increasingly safety-critical and socially-impactful applications, motivating the need to close the gap in model performance under varied, naturally occurring imaging conditions.…

In this paper, we present new optimization models for Support Vector Machine (SVM), with the aim of separating data points in two or more classes. The classification task is handled by means of nonlinear classifiers induced by kernel…

The goal of this paper is to analyze Long Short Term Memory (LSTM) neural networks from a dynamical system perspective. The classical recursive equations describing the evolution of LSTM can be recast in state space form, resulting in a…

Non-Volatile Memory (NVM) can deliver higher density and lower cost per bit when compared with DRAM. Its main drawback is that it is slower than DRAM. On the other hand, DRAM has scalability problems due to its cost and energy consumption.…

Persistent Memory (PM) technologies enable program recovery to a consistent state in a case of failure. To ensure this crash-consistent behavior, programs need to enforce persist ordering by employing mechanisms, such as logging and…

Flat combining (FC) is a synchronization paradigm in which a single thread, holding a global lock, collects requests by multiple threads for accessing a concurrent data structure and applies their combined requests to it. Although FC is…

Persistent memory provides high-performance data persistence at main memory. Memory writes need to be performed in strict order to satisfy storage consistency requirements and enable correct recovery from system crashes. Unfortunately,…

The crux of software transactional memory (STM) is to combine an easy-to-use programming interface with an efficient utilization of the concurrent-computing abilities provided by modern machines. But does this combination come with an…

In the non-volatile memory, ensuring the security and correctness of persistent data is fundamental. However, the security and persistence issues are usually studied independently in existing work. To achieve both data security and…

NVM is used as a new hierarchy in the storage system, due to its intermediate speed and capacity between DRAM, and its byte granularity. However, consistency problems emerge when we attempt to put DRAM, NVM, and disk together as an…

Resistive random-access memory (RRAM) is gaining popularity due to its ability to offer computing within the memory and its non-volatile nature. The unique properties of RRAM, such as binary switching, multi-state switching, and device…

DRAM-based main memories have read operations that destroy the read data, and as a result, must buffer large amounts of data on each array access to keep chip costs low. Unfortunately, system-level trends such as increased memory contention…

The large number of recent JEDEC DRAM standard releases and their increasing feature set makes it difficult for designers to rapidly upgrade the memory controller IPs to each new standard. Especially the hardware verification is challenging…

In the modern era of multicore processors, utilizing cores is a tedious job. Synchronization and communication among processors involve high cost. Software transaction memory systems (STMs) addresses this issues and provide better…

DIMM-compatible persistent memory unites memory and storage. Prior works utilize persistent memory either by combining the filesystem with direct access on memory mapped files or by managing it as a collection of objects while abolishing…

Detecting memory corruption vulnerabilities in stripped binaries requires recovering object semantics, interprocedural propagation, and feasible triggers from low-level, lossy representations. Recent LLM-based approaches improve code…

Transactional access to databases is an important abstraction allowing programmers to consider blocks of actions (transactions) as executing in isolation. The strongest consistency model is {\em serializability}, which ensures the atomicity…

Non-adversarial robustness, also known as natural robustness, is a property of deep learning models that enables them to maintain performance even when faced with distribution shifts caused by natural variations in data. However, achieving…

After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel's 3D XPoint DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the…

Software managed byte-addressable hybrid memory systems consisting of DRAMs and NVMMs offer a lot of flexibility to design efficient large scale data processing applications. Operating systems (OS) play an important role in enabling the…