Related papers: The gem5 Simulator: Version 20.0+
Across applications, DRAM is a significant contributor to the overall system power, with the DRAM access energy per bit up to three orders of magnitude higher compared to on-chip memory accesses. To improve the power efficiency, DRAM…
As blockchain-based systems see wider adoption, it becomes increasingly critical to ensure their reliability, security, and efficiency. Running simulations is an effective method of gaining insights on the existing systems and analyzing…
Mastering computational architectures is essential for developing fast and power-efficient programs. Our advanced simulator empowers both IT students and professionals to grasp the fundamentals of superscalar RISC-V processors, HW/SW…
In this paper we present Simgrid, a toolkit for the versatile simulation of large scale distributed systems, whose development effort has been sustained for the last fifteen years. Over this time period SimGrid has evolved from a…
Blockchain has attracted much attention from both academia and industry since emerging in 2008. Due to the inconvenience of the deployment of large-scale blockchains, blockchain simulators are used to facilitate blockchain design and…
This paper explores the impact of simulator accuracy on architecture design decisions in the general-purpose graphics processing unit (GPGPU) space. We perform a detailed, quantitative analysis of the most popular publicly available GPU…
Peer-to-peer networks consist of thousands or millions of nodes that might join and leave arbitrarily. The evaluation of new protocols in real environments is many times practically impossible, especially at design and testing stages. The…
System-level simulation is indispensable for developing and testing novel algorithms for 5G and future wireless networks, yet a gap persists between the needs of the machine learning re- search community and the available tooling. To…
This paper introduces LLMServingSim2.0, a system simulator designed for exploring heterogeneous hardware in large-scale LLM serving systems. LLMServingSim2.0 addresses two key limitations of its predecessor: (1) integrating hardware models…
The increasing growth of applications' memory capacity and performance demands has led the CPU vendors to deploy heterogeneous memory systems either within a single system or via disaggregation. For instance, systems like Intel's Knights…
Generative AI is increasing the productivity of software and hardware development across many application domains. In this work, we utilize the power of Large Language Models (LLMs) to develop a co-pilot agent for assisting gem5 users with…
MGSim is an open source discrete event simulator for on-chip hardware components, developed at the University of Amsterdam. It is intended to be a research and teaching vehicle to study the fine-grained hardware/software interactions on…
Cycle-accurate simulators are widely used to study systolic accelerators, yet their accuracy and usability are often limited by weak validation against real hardware and poor integration with modern ML compiler stacks. This paper presents…
Serverless computing is gaining traction as an attractive model for the deployment of a multitude of workloads in the cloud. Designing and building effective resource management solutions for any computing environment requires extensive…
Numerous blockchain simulators have been proposed to allow researchers to simulate mainstream blockchains. However, we have not yet found a testbed that enables researchers to develop and evaluate their new consensus algorithms or new…
The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintaining and executing computational saliency models. This work…
Quantum simulators are a foundational component of the quantum software ecosystem. They are widely used to develop and debug quantum programs, validate compiler transformations, and support empirical claims about correctness and…
Cloud Computing has established itself as an efficient and cost-effective paradigm for the execution of web-based applications, and scientific workloads, that need elasticity and on-demand scalability capabilities. However, the evaluation…
Edge computing, with its low latency, dynamic scalability, and location awareness, along with the convergence of computing and communication paradigms, has been successfully applied in critical domains such as industrial IoT, smart…
Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Nevertheless, the development of quantum computers is still in its…