Abstract

With aggressive scaling of device geometries, density of manufacturing faults is expected to increase. Therefore, yield of complex Multi-Processor Systems-on-Chips (MP-SoCs) will decrease due to higher probability of manufacturing defects especially, in dies with large area. Therefore, disintegration of large SoCs into smaller chips called chiplets will improve yield and cost of complex platform-based systems. This will also provide functional flexibility, modular scalability as well as the capability to integrate heterogeneous architectures and technologies in a single unit. However, with scaling of the number of chiplets in such a system, the shared resources in the system such as the interconnection fabric and memory modules will become performance bottlenecks. Additionally, the integration of heterogeneous chiplets operating at different frequencies and voltages can be challenging. State-of-the-art inter-chip communication requires power-hungry high-speed I/O circuits and data transfer over long wired traces on substrates. This increases energy consumption and latency while decreasing data bandwidth for chip-to-chip communication. In this paper, we explore the advances and the challenges of interconnecting a multi-chip system with millimeter-wave (mm-wave) wireless interconnects from a variety of perspectives spanning multiple aspects of the wireless interconnection design. Our discussion on the recent advances include aspects such as interconnection topology, physical layer, Medium Access Control (MAC) and routing protocols. We also present some potential paradigm-shifting applications as well as complementary technologies of wireless inter-chip communications.

Highlights

  • The silicon industry has exploited Moore’s law to satisfy the exponential growth in the functionality required for high-performance computing nodes such as servers and embedded systems

  • To demonstrate the impact of increase in number of chips in a multi-chip system we have considered an example where, a total of 64 cores in the system are disintegrated into multiple multicore chips

  • The Token Management Unit (TMU) has intelligence about when the token should arrive to which WI, and in case the token is not possessed by the specific WI within a certain time, the TMU regenerates the token correctly while avoiding duplication

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Summary

Introduction

The silicon industry has exploited Moore’s law to satisfy the exponential growth in the functionality required for high-performance computing nodes such as servers and embedded systems. In modern processors designed using advanced process technologies, the number of individual functional cores has increased to the order of hundreds and Network-on-Chip (NoC) has emerged as a scalable, modular interconnection architecture for such large multicore chips [3]. These smaller chips or chiplets are integrated onto a platform-based system and enable integration of chiplets from heterogeneous process technologies or functionalities This in turn, offers both process and functional flexibility in the design while eliminating the design and manufacturing complexity of large SoCs. Multicore multi-chip computing modules with multiple processors or chiplets can be found in a wide range of platform-based designs from servers to embedded systems. Athppel.t2h0r1o8,u8g, hx put per core decreases and packet energy increases with increase i4nofth35e number of multicore chips This indicates the need for an efficient inter-chip interconnection fabric. In the subsequent section we will focus on the inter-chip wireless topology design

The Inter-Chip Wireless Communication Topology
Physical Layer Design
Channel Characteristics
High-Bandwidth Antennas
Link Budget Analysis
Impact of Technology Scaling on Inter-Chip Wireless Interconnects
Wireless Communication Protocol
Flow Control and Deadlock Free Routing
Smart Channel Access
Robustness in MAC
CAD Tools and Simulation Environment
Qualitative Benefits of Wireless Interconnects
Comparison with Other Emerging Interconnect Technologies
Inter-Chip Wireless Communication in Neuromorphic Computing
10. Challenges of Inter-Chip Wireless Interconnects
Findings
11. Conclusions
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