Related papers: Rapid Recovery of Program Execution Under Power Fa…

Applications in the AI and HPC fields require much memory capacity, and the amount of energy consumed by main memory of server machines is ever increasing. Energy consumption of main memory can be greatly reduced by applying approximate…

Phase Change Memory (PCM) has rapidly progressed and surpassed Dynamic Random-Access Memory (DRAM) in terms of scalability and standby energy efficiency. Altering a PCM cell's state during writes demands substantial energy, posing a…

Embedded systems in safety-critical environments are continuously required to deliver more performance and functionality, while expected to provide verified safety guarantees. Nonetheless, platform-wide software verification (required for…

Spiking neural networks (SNNs) have shown a potential for having low energy with unsupervised learning capabilities due to their biologically-inspired computation. However, they may suffer from accuracy degradation if their processing is…

Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models. In this paper, we propose a lossy compression scheme for checkpoint constructions (called LC-Checkpoint). LC-Checkpoint…

PCM is a popular backing memory for DRAM main memory in tiered memory systems. PCM has asymmetric access energy; writes dominate reads. MLC asymmetry can vary by an order of magnitude. Many schemes have been developed to take advantage of…

As the size of deep learning models gets larger and larger, training takes longer time and more resources, making fault tolerance more and more critical. Existing state-of-the-art methods like CheckFreq and Elastic Horovod need to back up a…

In-Memory Computing (IMC) introduces a new paradigm of computation that offers high efficiency in terms of latency and power consumption for AI accelerators. However, the non-idealities and defects of emerging technologies used in advanced…

Performance and reliability are two prominent factors in the design of data storage systems. To achieve higher performance, recently storage system designers use DRAM-based buffers. The volatility of DRAM brings up the possibility of data…

In order to deliver high performance in cloud computing, we generally exploit and leverage RDMA (Remote Direct Memory Access) in networking and NVM (Non-Volatile Memory) in end systems. Due to no involvement of CPU, one-sided RDMA becomes…

Non-volatile memory (NVM) based compute-in-memory (CIM) accelerators have emerged as a sustainable solution to significantly boost energy efficiency and minimize latency for Deep Neural Networks (DNNs) inference due to their in-situ data…

Battery-less technology evolved to replace battery usage in space, deep mines, and other environments to reduce cost and pollution. Non-volatile memory (NVM) based processors were explored for saving the system state during a power failure.…

As LLM deployments scale over more hardware, the probability of a single failure in a system increases significantly, and cloud operators must consider robust countermeasures to handle these inevitable failures. A common recovery approach…

Smaller feature size, higher clock frequency and lower power consumption are of core concerns of today's nano-technology, which has been resulted by continuous downscaling of CMOS technologies. The resultant 'device shrinking' reduces the…

This paper presents Checkmate, a system that enables per-iteration checkpointing in DNN training without any training slowdown. The traditional approach to checkpointing requires a pause in training to copy model states to a separate…

In scientific computing and data science disciplines, it is often necessary to share application workflows and repeat results. Current tools containerize application workflows, and share the resulting container for repeating results. These…

We describe verification techniques for embedded memory systems using efficient memory modeling (EMM), without explicitly modeling each memory bit. We extend our previously proposed approach of EMM in Bounded Model Checking (BMC) for a…

Production MPI codes need checkpoint-restart (CPR) support. Clearly, checkpoint-restart libraries must be fault tolerant lest they open up a window of vulnerability for failures with byzantine outcomes. But, certain popular libraries that…

Ensuring accurate violation detection in power systems is paramount for operational reliability. This paper introduces an enhanced voltage recovery violation index (EVRVI), a comprehensive index designed to quantify fault-induced delayed…

A reliable and scalable mechanism to provide protection against a link or node failure has additional requirements in the context of SDN and OpenFlow. Not only it has to minimize the load on the controller, but it must be able to react even…