Related papers: Practical Fine-grained Privilege Separation in Mul…
Increasing investment in computing technologies and the advancements in silicon technology has fueled rapid growth in advanced driver assistance systems (ADAS) and corresponding SoC developments. An ADAS SoC represents a heterogeneous…
Mixed-criticality systems, where multiple systems with varying criticality-levels share a single hardware platform, require isolation between tasks with different criticality-levels. Isolation can be achieved with software-based solutions…
The trade-off between coarse- and fine-grained locking is a well understood issue in operating systems. Coarse-grained locking provides lower overhead under low contention, fine-grained locking provides higher scalability under contention,…
We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and…
The computing paradigm invented for processing a small amount of data on a single segregated processor cannot meet the challenges set by the present-day computing demands. The paper proposes a new computing paradigm (extending the old one…
Motivated by recent distributed systems technology, Aguilera et al. introduced a hybrid model of distributed computing, called message-and-memory model or m&m model for short [1]. In this model, processes can communicate by message passing…
In this work, we present novel protocols over rings for semi-honest secure three-party computation (3PC) and malicious four-party computation (4PC) with one corruption. While most existing works focus on improving total communication…
Modern computer designs support composite prefetching, where multiple individual prefetcher components are used to target different memory access patterns. However, multiple prefetchers competing for resources can drastically hurt…
The growing memory footprints of cloud and big data applications mean that data center CPUs can spend significant time waiting for memory. An attractive approach to improving performance in such centralized compute settings is to employ…
We introduce a mixed integer program (MIP) for assigning importance scores to each neuron in deep neural network architectures which is guided by the impact of their simultaneous pruning on the main learning task of the network. By…
Applications with safety requirements have become ubiquitous nowadays and can be found in edge devices of all kinds. However, microcontrollers in those devices, despite offering moderate performance by implementing multicores and cache…
In the case of multi-threading as found in contemporary programming languages, parallel processes are interleaved according to what is known as a process-scheduling policy in the field of operating systems. In a previous paper, we extend…
We propose a type system to analyze the time consumed by multi-threaded imperative programs with a shared global memory, which delineates a class of safe multi-threaded programs. We demonstrate that a safe multi-threaded program runs in…
Typically, a memory request from a processor may need to go through many intermediate interconnect routers, directory node, owner node, etc before it is finally serviced. Current multiprocessors do not give preference to any particular…
As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and…
Microservice architecture is widely adopted among distributed systems. It follows the modular approach that decomposes large software applications into independent services. Kubernetes has become the standard tool for managing these…
Throughput limitations of existing blockchain architectures are one of the most significant hurdles for their wide-spread adoption. Attempts to address this challenge include layer-2 solutions, such as Bitcoin's Lightning or Ethereum's…
With power consumption becoming a critical processor design issue, specialized architectures for low power processing are becoming popular. Several studies have shown that neural networks can be used for signal processing and pattern…
Large-scale parallel numerical simulations are essential for a wide range of engineering problems that involve complex, coupled physical processes interacting across a broad range of spatial and temporal scales. The data structures involved…
Distributed computing frameworks such as MapReduce have become essential for large-scale data processing by decomposing tasks across multiple nodes. The multi-access distributed computing (MADC) model further advances this paradigm by…