Related papers: Chiplets on Wheels: Review Paper on Holistic Chipl…
This paper focuses on the simulation of multi-die System-on-Chip (SoC) architectures using VisualSim, emphasizing chiplet-based system modeling and performance analysis. Chiplet technology presents a promising alternative to traditional…
A chiplet is an integrated circuit that encompasses a well-defined subset of an overall system's functionality. In contrast to traditional monolithic system-on-chips (SoCs), chiplet-based architecture can reduce costs and increase…
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…
Enhancing performance while reducing costs is the fundamental design philosophy of integrated circuits (ICs). With advancements in packaging technology, interposer-based chiplet architecture has emerged as a promising solution. Chiplet…
Vision Transformers (ViTs) have established new performance benchmarks in vision tasks such as image recognition and object detection. However, these advancements come with significant demands for memory and computational resources,…
Achieving high performance, energy efficiency, and cost-effectiveness while maintaining architectural flexibility is a critical challenge in the development and deployment of edge AI devices. Monolithic SoC designs struggle with this…
Silicon-based CMOS technologies are predicted to reach their ultimate limits by the middle of the next decade. Research on nanotechnologies is actively conducted, in a world-wide effort to develop new technologies able to maintain the…
We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems from how chiplets technology is becoming integral to…
Recently, hardware technology has rapidly evolved pertaining to domain-specific applications/architectures. Soon, processors may be composed of a large collection of vendor-independent IP specialized for application-specific algorithms,…
Large language models (LLMs) such as OpenAI's ChatGPT and Google's Gemini have demonstrated unprecedented capabilities of autoregressive AI models across multiple tasks triggering disruptive technology innovations around the world. However,…
Decades of progress in energy-efficient and low-power design have successfully reduced the operational carbon footprint in the semiconductor industry. However, this has led to an increase in embodied emissions, encompassing carbon emissions…
Multi-chip integration is widely recognized as the extension of Moore's Law. Cost-saving is a frequently mentioned advantage, but previous works rarely present quantitative demonstrations on the cost superiority of multi-chip integration…
Chiplet architectures are on the rise as they promise to overcome the scaling challenges of monolithic chips. A key component of such architectures is an efficient inter-chiplet interconnect (ICI). The ICI design space is huge as there are…
Driven by a need for ever increasing chip performance and inclusion of innovative features, a growing number of semiconductor companies are opting for all-inclusive System-on-Chip (SoC) architectures. Although Moore's Law has been able to…
Industry adoption of chiplets has been growing as chiplets are a cost-effective option for making large, high-performance systems. Consequently, partitioning large systems into chiplets is increasingly important. In this work, we introduce…
The advent of chiplet technology introduces cutting-edge opportunities for constructing highly heterogeneous platforms with specialized accelerators. However, the HPC community currently lacks expertise in hardware development, a gap that…
Centralized electrical/electronic architectures and High-Performance Computers (HPCs) are redefining automotive software development, challenging traditional microcontroller-based approaches. Ensuring real-time, safety, and scalability in…
Due to reduced manufacturing yields, traditional monolithic chips cannot keep up with the compute, memory, and communication demands of data-intensive applications, such as rapidly growing deep neural network (DNN) models. Chiplet-based…
A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address…
The amount of software in modern cars is increasing continuously with traditional electric/electronic (E/E) architectures reaching their limit when deploying complex applications, e.g., regarding bandwidth or computational power. To…