Related papers: HMM-V: Heterogeneous Memory Management for Virtual…

Emerging Persistent Memory technologies (also PM, Non-Volatile DIMMs, Storage Class Memory or SCM) hold tremendous promise for accelerating popular data-management applications like in-memory databases. However, programmers now need to deal…

Software-managed heterogeneous memory (HM) provides a promising solution to increase memory capacity and cost efficiency. However, to release the performance potential of HM, we face a problem of data management. Given an application with…

The advent of non-volatile memory (NVM) technologies like PCM, STT, memristors and Fe-RAM is believed to enhance the system performance by getting rid of the traditional memory hierarchy by reducing the gap between memory and storage. This…

Processing-in-Memory (PIM) architectures offer promising solutions for efficiently handling AI applications in energy-constrained edge environments. While traditional PIM designs enhance performance and energy efficiency by reducing data…

Deployment of modern TinyML tasks on small battery-constrained IoT devices requires high computational energy efficiency. Analog In-Memory Computing (IMC) using non-volatile memory (NVM) promises major efficiency improvements in deep neural…

Modern computing systems are embracing non-volatile memory (NVM) to implement high-capacity and low-cost main memory. Elevated operating voltages of NVM accelerate the aging of CMOS transistors in the peripheral circuitry of each memory…

Embedded machine learning (ML) systems have now become the dominant platform for deploying ML serving tasks and are projected to become of equal importance for training ML models. With this comes the challenge of overall efficient…

A large language model (LLM) is one of the most important emerging machine learning applications nowadays. However, due to its huge model size and runtime increase of the memory footprint, LLM inferences suffer from the lack of memory…

Discrete GPU accelerators, while providing massive computing power for supercomputers and data centers, have their separate memory domain. Explicit memory management across device and host domains in programming is tedious and error-prone.…

Shared virtual memory (SVM) is key in heterogeneous systems on chip (SoCs), which combine a general-purpose host processor with a many-core accelerator, both for programmability and to avoid data duplication. However, SVM can bring a…

With wide spread acceptance of virtualization, virtual machines (VMs) find their presence in various applications such as Network Address Translation (NAT) servers, firewall servers and MapReduce applications. Typically, in these…

Scalable nonvolatile memory DIMMs will finally be commercially available with the release of the Intel Optane DC Persistent Memory Module (or just "Optane DC PMM"). This new nonvolatile DIMM supports byte-granularity accesses with access…

Repeated off-chip memory accesses to DRAM drive up operating power for data-intensive applications, and SRAM technology scaling and leakage power limits the efficiency of embedded memories. Future on-chip storage will need higher density…

NVMe(Non-Volatile Memory Express) is an industry standard for solid-state drives (SSDs) that has been widely adopted in data centers. NVMe virtualization is crucial in cloud computing as it allows for virtualized NVMe devices to be used by…

This paper addresses the impact of Virtual Memory Streaming (VMS) technique in provisioning virtual machines (VMs) in cloud environment. VMS is a scaling virtualization technology that allows different virtual machines rapid scale, high…

Optimal deployment of deep neural networks (DNNs) on state-of-the-art Systems-on-Chips (SoCs) is crucial for tiny machine learning (TinyML) at the edge. The complexity of these SoCs makes deployment non-trivial, as they typically contain…

This paper introduces a novel approach in neuromorphic computing, integrating heterogeneous hardware nodes into a unified, massively parallel architecture. Our system transcends traditional single-node constraints, harnessing the neural…

With the imminent slowing down of DRAM scaling, Phase Change Memory (PCM) is emerging as a lead alternative for main memory technology. While PCM achieves low energy due to various technology-specific advantages, PCM is significantly slower…

Efficient virtual machine (VM) management can dramatically reduce energy consumption in data centers. Existing VM management algorithms fall into two categories based on whether the VMs' resource demands are assumed to be static or dynamic.…

This paper introduces Out of Hypervisor (OoH), a new research axis close to nested virtualization. Instead of emulating a full virtual hardware inside a VM to support a hypervisor, the OoH principle is to individually expose current…