Achieving Functional Correctness in Large Interconnect Systems.

In today's semi-conductor industry, large chip-multiprocessors and systems-on-chip are being developed, integrating a large number of components on a single chip. The sheer size of these designs and the intricacy of the communication patterns they exhibit have propelled the development of network-on-chip (NoC) interconnects as the basis for the communication infrastructure in these systems. Faced with the interconnect's growing size and complexity, several challenges hinder its effective validation. During the interconnect's development, the functional verification process relies heavily on the use of emulation and post-silicon validation platforms. However, detecting and debugging errors on these platforms is a difficult endeavour due to the limited observability, and in turn the low verification capabilities, they provide. Additionally, with the inherent incompleteness of design-time validation efforts, the potential of design bugs escaping into the interconnect of a released product is also a concern, as these bugs can threaten the viability of the entire system. This dissertation provides solutions to enable the development of functionally correct interconnect designs. We first address the challenges encountered during design-time verification efforts, by providing two complementary mechanisms that allow emulation and post-silicon verification frameworks to capture a detailed overview of the functional behaviour of the interconnect. Our first solution re-purposes the contents of in-flight traffic to log debug data from the interconnect's execution. This approach enables the validation of the interconnect using synthetic traffic workloads, while attaining over 80% observability of the routes followed by packets and capturing valuable debugging information. We also develop an alternative mechanism that boosts observability by taking periodic snapshots of execution, thus extending the verification capabilities to run both synthetic traffic and real-application workloads. The collected snapshots enhance detection and debugging support, and they provide observability of over 50% of packets and reconstructs at least half of each of their routes. Moreover, we also develop error detection and recovery solutions to address the threat of design bugs escaping into the interconnect's runtime operation. Our runtime techniques can overcome communication errors without needing to store replicate copies of all in-flight packets, thereby achieving correctness at minimal area costsPhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116741/1/rawanak_1.pd

eBPF: A New Approach to Cloud-Native Observability, Networking and Security for Current (5G) and Future Mobile Networks (6G and Beyond)

Modern mobile communication networks and new service applications are deployed on cloud-native platforms. Kubernetes (K8s) is the de facto distributed operating system for container orchestration, and the extended version of the Berkeley Packet Filter (eBPF)- in the Linux (and MS Windows) kernel- is fundamentally changing the approach to cloud-native networking, security, and observability. In this paper, we introduce what eBPF is, its potential for Telco cloud, and review some of the most promising pricing and billing models applied to this revolutionary operating system (OS) technology. These models include schemes based on a data source usage model or the number of eBPF agents deployed on the network, linked to specific eBPF modules. These modules encompass network observability, runtime security, and power dissipation monitoring. Next, we present our eBPF platform, named Sauron in this work, and demonstrate how eBPF allows us to write custom code and dynamically load eBPF programs into the kernel. These programs enable us to estimate the energy consumption of cloud-native functions, derive performance counters and gauges for transport networks, 5G applications, and non-access stratum protocols. Additionally, we can detect and respond to unauthorized access to cloud-native resources in real-time using eBPF. Our experimental results demonstrate the technical feasibility of eBPF in achieving highly performant monitoring, observability, and security tooling for current mobile networks (5G, 5G Advanced) as well as future networks (6G and beyond)

DiAMOND:Distributed Alteration of Messages for On-Chip Network Debug

Abstract-During emulation and post-silicon validation of networks-on-chip (NoCs), lack of observability of internal operations hinders the detection and debugging of functional bugs. Verifying the correctness of the control-flow portion of the NoC requires tests that exercise its functionality, while abstracting the data content of traffic. We propose a methodology where network packets are repurposed for the storage of debug information collected during execution. Debug data pertaining to each packet is collected at routers along its path and stored by replacing the packet's original data content. Our solution is coupled with a detection scheme consisting of small checkers that monitor execution and flag bugs. Upon bug detection, we analyze the debug information to reconstruct network traffic. We also provide relevant statistics for debugging, such as packet interactions and packet latencies, per router. In our experiments, this approach allows us to reconstruct over 80% of the packets' routes. Moreover, the obtained statistics facilitate debugging erroneous network behavior and identifying performance bottlenecks

Software-based and regionally-oriented traffic management in Networks-on-Chip

Since the introduction of chip-multiprocessor systems, the number of integrated cores has been steady growing and workload applications have been adapted to exploit the increasing parallelism. This changed the importance of efficient on-chip communication significantly and the infrastructure has to keep step with these new requirements. The work at hand makes significant contributions to the state-of-the-art of the latest generation of such solutions, called Networks-on-Chip, to improve the performance, reliability, and flexible management of these on-chip infrastructures

Runtime Adaptive System-on-Chip Communication Architecture

The adaptive system provides adaptivity both in the system-level and in the architecture-level. The system-level adaptation is provided using a runtime application mapping. The architecture-level adaptation is implemented by using several novel methodologies to increase the resource utilization of the underlying silicon fabric, i.e. sharing the Virtual Channel Buffers among different output ports. To achieve successful runtime adaptation, a runtime observability infrastructure is included

Decompose and Conquer: Addressing Evasive Errors in Systems on Chip

Modern computer chips comprise many components, including microprocessor cores, memory modules, on-chip networks, and accelerators. Such system-on-chip (SoC) designs are deployed in a variety of computing devices: from internet-of-things, to smartphones, to personal computers, to data centers. In this dissertation, we discuss evasive errors in SoC designs and how these errors can be addressed efficiently. In particular, we focus on two types of errors: design bugs and permanent faults. Design bugs originate from the limited amount of time allowed for design verification and validation. Thus, they are often found in functional features that are rarely activated. Complete functional verification, which can eliminate design bugs, is extremely time-consuming, thus impractical in modern complex SoC designs. Permanent faults are caused by failures of fragile transistors in nano-scale semiconductor manufacturing processes. Indeed, weak transistors may wear out unexpectedly within the lifespan of the design. Hardware structures that reduce the occurrence of permanent faults incur significant silicon area or performance overheads, thus they are infeasible for most cost-sensitive SoC designs. To tackle and overcome these evasive errors efficiently, we propose to leverage the principle of decomposition to lower the complexity of the software analysis or the hardware structures involved. To this end, we present several decomposition techniques, specific to major SoC components. We first focus on microprocessor cores, by presenting a lightweight bug-masking analysis that decomposes a program into individual instructions to identify if a design bug would be masked by the program's execution. We then move to memory subsystems: there, we offer an efficient memory consistency testing framework to detect buggy memory-ordering behaviors, which decomposes the memory-ordering graph into small components based on incremental differences. We also propose a microarchitectural patching solution for memory subsystem bugs, which augments each core node with a small distributed programmable logic, instead of including a global patching module. In the context of on-chip networks, we propose two routing reconfiguration algorithms that bypass faulty network resources. The first computes short-term routes in a distributed fashion, localized to the fault region. The second decomposes application-aware routing computation into simple routing rules so to quickly find deadlock-free, application-optimized routes in a fault-ridden network. Finally, we consider general accelerator modules in SoC designs. When a system includes many accelerators, there are a variety of interactions among them that must be verified to catch buggy interactions. To this end, we decompose such inter-module communication into basic interaction elements, which can be reassembled into new, interesting tests. Overall, we show that the decomposition of complex software algorithms and hardware structures can significantly reduce overheads: up to three orders of magnitude in the bug-masking analysis and the application-aware routing, approximately 50 times in the routing reconfiguration latency, and 5 times on average in the memory-ordering graph checking. These overhead reductions come with losses in error coverage: 23% undetected bug-masking incidents, 39% non-patchable memory bugs, and occasionally we overlook rare patterns of multiple faults. In this dissertation, we discuss the ideas and their trade-offs, and present future research directions.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147637/1/doowon_1.pd