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Sparse generalized matrix-matrix multiplication (SpGEMM) is a fundamental operation for real-world network analysis. With the increasing size of real-world networks, the single-machine-based SpGEMM approach cannot perform SpGEMM on…
Transformers have become the foundation of numerous state-of-the-art AI models across diverse domains, thanks to their powerful attention mechanism for modeling long-range dependencies. However, the quadratic scaling complexity of attention…
This paper summarizes the ideas and key concepts in MISE (Memory Interference-induced Slowdown Estimation), which was published in HPCA 2013 [97], and examines the work's significance and future potential. Applications running concurrently…
Future wireless networks will progressively displace service provisioning towards the edge to accommodate increasing growth in traffic. This paradigm shift calls for smart policies to efficiently share network resources and ensure service…
Heterogeneous systems have become one of the most common architectures today, thanks to their excellent performance and energy consumption. However, due to their heterogeneity they are very complex to program and even more to achieve…
Ensuring the confidentiality and integrity of DNN accelerators is paramount across various scenarios spanning autonomous driving, healthcare, and finance. However, current security approaches typically require extensive hardware resources,…
Deterministic databases enable scalable replicated systems by executing transactions in a predetermined order. However, existing designs fail to capture transaction dependencies, leading to insufficient scheduling, high abort rates, and…
Numerous applications such as financial transactions (e.g., stock trading) are write-heavy in nature. The shift from reads to writes in web applications has also been accelerating in recent years. Write-ahead-logging is a common approach…
Process Execution Engines are a vital part of Business Process Management (BPM) and Manufacturing Orchestration Management (MOM), as they allow the business or manufacturing logic (expressed in a graphical notation such as BPMN) to be…
SQL-on-Hadoop systems, query optimization, data distribution over multiple nodes and parallelization techniques are few of the areas under extreme research these days. Big names like Amazon, Google, Microsoft and many more are working on…
Managing the transactions in real time distributed computing system is not easy, as it has heterogeneously networked computers to solve a single problem. If a transaction runs across some different sites, it may commit at some sites and may…
We present Saguaro, a permissioned blockchain system designed specifically for edge computing networks. Saguaro leverages the hierarchical structure of edge computing networks to reduce the overhead of wide-area communication by presenting…
Motivated by the benefits of multi-energy integration, this paper establishes a bi-level two-stage framework based on transactive control, in order to achieve optimal energy provision among interconnected multi-energy systems (MESs). At the…
Parallel architectures are continually increasing in performance and scale, while underlying algorithmic infrastructure often fail to take full advantage of available compute power. Within the context of MPI, irregular communication…
Recent advances have improved the throughput and latency of blockchains by processing transactions accessing different parts of the state concurrently. However, these systems are unable to concurrently process (a) transactions accessing the…
Multiprocess systems, including grid systems, multiprocessors and multicore computers, incorporate a variety of specialized hardware and software mechanisms, which speed computation, but result in complex memory behavior. As a consequence,…
This paper presents a scheme for efficient channel usage between simulator and accelerator where the accelerator models some RTL sub-blocks in the accelerator-based hardware/software co-simulation while the simulator runs transaction-level…
Data-driven analysis is important in virtually every modern organization. Yet, most data is underutilized because it remains locked in silos inside of organizations; large organizations have thousands of databases, and billions of files…
This paper aims to categorize bank transactions using weak supervision, natural language processing, and deep neural network techniques. Our approach minimizes the reliance on expensive and difficult-to-obtain manual annotations by…
In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a single-node non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to…