Related papers: Work-in-Progress: A Simulation Framework for Domai…
Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from load imbalance during their execution on high-performance…
The rapid advancements in AI, scientific computing, and high-performance computing (HPC) have driven the need for versatile and efficient hardware accelerators. Existing tools like SCALE-Sim v2 provide valuable cycle-accurate simulations…
Optimizing high-performance power electronic equipment, such as power converters, requires multiscale simulations that incorporate the physics of power semiconductor devices and the dynamics of other circuit components, especially in…
SoCs are now designed with their own AI accelerator segment to accommodate the ever-increasing demand of Deep Learning (DL) applications. With powerful MAC engines for matrix multiplications, these accelerators show high computing…
In this study, we introduce a methodology for automatically transforming user applications in the radar and communication domain written in C/C++ based on dynamic profiling to a parallel representation targeted for a heterogeneous SoC. We…
Emerging applications in the IoT domain require ultra-low-power and high-performance end-nodes to deal with complex near-sensor-data analytics. Domains such as audio, radar, and Structural Health Monitoring require many computations to be…
Home Energy Management Systems (HEMS) are being actively developed for both individual houses and communities to support demand response in on-grid operation, and ensure resilience during off-grid scenarios. However, most simulators used…
3D integration offers key advantages in improving system performance and efficiency for the End-of-Scaling era. It enables the incorporation of heterogeneous system components and disparate technologies, eliminates off-chip communication…
In recent years, there has been tremendous advances in hardware acceleration of deep neural networks. However, most of the research has focused on optimizing accelerator microarchitecture for higher performance and energy efficiency on a…
In this paper is proposed a technique to integrate and simulate a dynamic memory in a multiprocessor framework based on C/C++/SystemC. Using host machine's memory management capabilities, dynamic data processing is supported without…
This article introduces a highly parallel algorithm for molecular dynamics simulations with short-range forces on single node multi- and many-core systems. The algorithm is designed to achieve high parallel speedups for strongly…
Performance-, power-, and energy-aware scheduling techniques play an essential role in optimally utilizing processing elements (PEs) of heterogeneous systems. List schedulers, a class of low-complexity static schedulers, have commonly been…
Processing data received as a stream is a task commonly performed by modern embedded devices, in a wide range of applications such as multimedia (encoding/decoding/ playing media), networking (switching and routing), digital security,…
In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…
Resource-limited robots face significant challenges in executing computationally intensive tasks, such as locomotion and manipulation, particularly for real-time optimal control algorithms like Model Predictive Control (MPC). This paper…
Recently the hardware emulation technique has emerged as a promising approach to accelerating hardware verification/debugging process. To fully evaluate the powerfulness of the emulation approach and demonstrate its potential impact, we…
Top-tier parallel computing clusters continue to accumulate more and more computational power with more and better CPUs and Networks. This allows, especially for environmental simulations, computations with larger domain sizes and better…
Domain-specific systems-on-chip, a class of heterogeneous many-core systems, are recognized as a key approach to narrow down the performance and energy-efficiency gap between custom hardware accelerators and programmable processors.…
Fast-evolving artificial intelligence (AI) algorithms such as large language models have been driving the ever-increasing computing demands in today's data centers. Heterogeneous computing with domain-specific architectures (DSAs) brings…
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…