Related papers: H-MBR: Hypervisor-level Memory Bandwidth Reservati…
Chip multiprocessors (CMPs) are ubiquitous in most of today's computing fields. Although they provide noticeable benefits in terms of performance, cost and power efficiency, they also introduce some new issues. In this paper we analyze how…
Consumer-electronics systems are becoming increasingly complex as the number of integrated applications is growing. Some of these applications have real-time requirements, while other non-real-time applications only require good average…
We propose overcoming the memory capacity limitation of GPUs with high-capacity Storage-Class Memory (SCM) and DRAM cache. By significantly increasing the memory capacity with SCM, the GPU can capture a larger fraction of the memory…
To reduce LLM costs and latency, semantic caching systems must accurately identify when a new prompt matches a cached one. Current methods often rely on simplistic similarity measures, which limit their effectiveness. We introduce…
Overparameterized machine learning (ML) methods such as neural networks may be prohibitively resource intensive for devices with limited computational capabilities. Hyperdimensional computing (HDC) is an emerging resource efficient and…
A fundamental challenge in multi- and many-core systems is the correct execution of concurrent access to shared data. A common drawback from existing synchronization mechanisms is the loss of data locality as the shared data is transferred…
Cloud stacks must isolate application components, while permitting efficient data sharing between components deployed on the same physical host. Traditionally, the MMU enforces isolation and permits sharing at page granularity. MMU…
As the communication requirements of current and future Multiprocessor Systems on Chips (MPSoCs) continue to increase, scalable communication architectures are needed to support the heavy communication demands of the system. This is…
This work uses visual knowledge discovery in parallel coordinates to advance methods of interpretable machine learning. The graphic data representation in parallel coordinates made the concepts of hypercubes and hyperblocks (HBs) simple to…
With the skyrocketing costs of GPUs and their virtual instances in the cloud, there is a significant desire to use CPUs for large language model (LLM) inference. KV cache update, often implemented as allocation, copying, and in-place…
On embedded processors that are increasingly equipped with multiple CPU cores, static hardware partitioning is an established means of consolidating and isolating workloads onto single chips. This architectural pattern is suitable for…
Modern cloud computing workloads are composed of multiresource jobs that require a variety of computational resources in order to run, such as CPU cores, memory, disk space, or hardware accelerators. A single cloud server can typically run…
Modern cloud computing workloads are composed of multiresource jobs that require a variety of computational resources in order to run, such as CPU cores, memory, disk space, or hardware accelerators. A single cloud server can typically run…
Existing state-of-the-art vertical autoscalers for containerized environments are traditionally built for cloud applications, which might behave differently than HPC workloads with their dynamic resource consumption. In these environments,…
Containers are used by an increasing number of Internet service providers to deploy their applications in multi-access edge computing (MEC) systems. Although container-based virtualization technologies significantly increase application…
Modern airborne operating systems implement the concept of robust time and resource partitioning imposed by the standards for aerospace and airborne-embedded software systems, such as ARINC 653. While these standards do provide a…
Spectral clustering is a celebrated algorithm that partitions objects based on pairwise similarity information. While this approach has been successfully applied to a variety of domains, it comes with limitations. The reason is that there…
The memory demand of virtual machines (VMs) is increasing, while DRAM has limited capacity and high power consumption. Non-volatile memory (NVM) is an alternative to DRAM, but it has high latency and low bandwidth. We observe that the VM…
Uncertainties in balancing generation and load in low-carbon industrial microgrids (IMGs) make hybrid energy storage systems (HESS) crucial for their stable and economic operation. Existing model predictive control (MPC) techniques…
The conventional model of resource allocation in HPC systems is static. Thus, a job cannot leverage newly available resources in the system or release underutilized resources during the execution. In this paper, we present Kub, a…