Related papers: LearnedCache: An eBPF-Integrated Perceptron-Based …

We present LearnedFTL, a new on-demand page-level flash translation layer (FTL) design, which employs learned indexes to improve the address translation efficiency of flash-based SSDs. The first of its kind, it reduces the number of double…

NLP Workbench is a web-based platform for text mining that allows non-expert users to obtain semantic understanding of large-scale corpora using state-of-the-art text mining models. The platform is built upon latest pre-trained models and…

New PCI-e flash cards and SSDs supporting over 100,000 IOPs are now available, with several usecases in the design of a high performance storage system. By using an array of flash chips, arranged in multiple banks, large capacities are…

Computation offloading at lower time and lower energy consumption is crucial for resource limited mobile devices. This paper proposes an offloading decision-making model using federated learning. Based on the task type and the user input,…

The computing in the network (COIN) paradigm has emerged as a potential solution for computation-intensive applications like the metaverse by utilizing unused network resources. The blockchain (BC) guarantees task-offloading privacy, but…

Emerging high performance non-volatile memories recall the importance of efficient file system design. To avoid the virtual file system (VFS) and syscall overhead as in these kernel-based file systems, recent works deploy file systems…

Broad adoption of Large Language Models (LLM) demands rapid expansions of cloud LLM inference clusters, leading to accumulation of embodied carbon$-$the emissions from manufacturing and supplying IT assets$-$that mostly concentrate on…

With the advent of byte-addressable memory devices, such as CXL memory, persistent memory, and storage-class memory, tiered memory systems have become a reality. Page migration is the de facto method within operating systems for managing…

Linux kernel is a huge code base with enormous number of subsystems and possible configuration options that results in unmanageable complexity of elaborating an efficient configuration. Machine Learning (ML) is approach/area of learning…

In kernel-centric operations, the uprobe component of eBPF frequently encounters performance bottlenecks, largely attributed to the overheads borne by context switches. Transitioning eBPF operations to user space bypasses these hindrances,…

As memory capacity has outstripped TLB coverage, large data applications suffer from frequent page table walks. We investigate two complementary techniques for addressing this cost: reducing the number of accesses required and reducing the…

The growing reliance on large-scale data centers to run resource-intensive workloads has significantly increased the global carbon footprint, underscoring the need for sustainable computing solutions. While container orchestration platforms…

Flash memory is widely used as the secondary storage in lightweight computing devices due to its outstanding advantages over magnetic disks. Flash memory has many access characteristics different from those of magnetic disks, and how to…

With the growing demand for latency-critical and computation-intensive Internet of Things (IoT) services, the IoT-oriented network architecture, mobile edge computing (MEC), has emerged as a promising technique to reinforce the computation…

Cache plays a critical role in reducing the performance gap between CPU and main memory. A modern multi-core CPU generally employs a multi-level hierarchy of caches, through which the most recently and frequently used data are maintained in…

Edge computing is a fast-growing computing paradigm where data is processed at the local site where it is generated, close to the end-devices. This can benefit a set of disruptive applications like autonomous driving, augmented reality, and…

Multi-core processors improve performance, but they can create unpredictability owing to shared resources such as caches interfering. Cache partitioning is used to alleviate the Worst-Case Execution Time (WCET) estimation by isolating the…

With the aim of obtaining time/space improvements in classic Data Structures, an emerging trend is to combine Machine Learning techniques with the ones proper of Data Structures. This new area goes under the name of Learned Data Structures.…

We make three observations in modern processors: (1) LLC capacity is getting larger (up to 1GB); (2) core counts are increasing (up to 128 cores), accumulating a more significant amount of private L2 cache capacity on the chip; and (3)…

In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as \textsc{LRU} can perform far worse than the offline optimum. Existing learning-based caching systems improve hit rates mainly through…