Virtualizing Network Processors

This paper considers the problem of virtualizing the resources of a network processor (NP) in order to allow multiple third-parties to execute their own virtual router software on a single physical router at the same time. Our broad interest is in designing such a router capable of supporting virtual networking. We discuss the issues and challenges involved in this virtualization, and then describe specific techniques for virtualizing both the control and data-plane processors on NPs. For Intel IXP NPs in particular, we present a dynamic, macro-based technique for virtualization that allows multiple virtual routers to run on multiple data plane processors (or micro-engines) while maintaining memory isolation and enforcing memory bandwidth allocations

Packet Transactions: High-level Programming for Line-Rate Switches

Many algorithms for congestion control, scheduling, network measurement, active queue management, security, and load balancing require custom processing of packets as they traverse the data plane of a network switch. To run at line rate, these data-plane algorithms must be in hardware. With today's switch hardware, algorithms cannot be changed, nor new algorithms installed, after a switch has been built. This paper shows how to program data-plane algorithms in a high-level language and compile those programs into low-level microcode that can run on emerging programmable line-rate switching chipsets. The key challenge is that these algorithms create and modify algorithmic state. The key idea to achieve line-rate programmability for stateful algorithms is the notion of a packet transaction : a sequential code block that is atomic and isolated from other such code blocks. We have developed this idea in Domino, a C-like imperative language to express data-plane algorithms. We show with many examples that Domino provides a convenient and natural way to express sophisticated data-plane algorithms, and show that these algorithms can be run at line rate with modest estimated die-area overhead.Comment: 16 page

Optimizing energy-efficiency for multi-core packet processing systems in a compiler framework

Network applications become increasingly computation-intensive and the amount of traffic soars unprecedentedly nowadays. Multi-core and multi-threaded techniques are thus widely employed in packet processing system to meet the changing requirement. However, the processing power cannot be fully utilized without a suitable programming environment. The compilation procedure is decisive for the quality of the code. It can largely determine the overall system performance in terms of packet throughput, individual packet latency, core utilization and energy efficiency. The thesis investigated compilation issues in networking domain first, particularly on energy consumption. And as a cornerstone for any compiler optimizations, a code analysis module for collecting program dependency is presented and incorporated into a compiler framework. With that dependency information, a strategy based on graph bi-partitioning and mapping is proposed to search for an optimal configuration in a parallel-pipeline fashion. The energy-aware extension is specifically effective in enhancing the energy-efficiency of the whole system. Finally, a generic evaluation framework for simulating the performance and energy consumption of a packet processing system is given. It accepts flexible architectural configuration and is capable of performingarbitrary code mapping. The simulation time is extremely short compared to full-fledged simulators. A set of our optimization results is gathered using the framework

Fast Packet Processing on High Performance Architectures

The rapid growth of Internet and the fast emergence of new network applications have brought great challenges and complex issues in deploying high-speed and QoS guaranteed IP network. For this reason packet classication and network intrusion detection have assumed a key role in modern communication networks in order to provide Qos and security. In this thesis we describe a number of the most advanced solutions to these tasks. We introduce NetFPGA and Network Processors as reference platforms both for the design and the implementation of the solutions and algorithms described in this thesis. The rise in links capacity reduces the time available to network devices for packet processing. For this reason, we show different solutions which, either by heuristic and randomization or by smart construction of state machine, allow IP lookup, packet classification and deep packet inspection to be fast in real devices based on high speed platforms such as NetFPGA or Network Processors

Network Processors and Next Generation Networks: Design, Applications, and Perspectives

Network Processors (NPs) are hardware platforms born as appealing solutions for packet processing devices in networking applications. Nowadays, a plethora of solutions exists, with no agreement on a common architecture. Each vendor has proposed its specific solution and no official standard still exists. The common features of all proposals are a hierarchy of processors, with a general purpose processor and several units specialized for packet processing, a series of memory devices with different sizes and latencies, a low-level programmability. The target is a platform for networking applications with low time to market and high time in market, thanks to a high flexibility and a programmability simpler than that of ASICs, for example. After about ten years since the "birth" of network processors, this research activity wants to make an analytical balance of their development and usage. Many authoritative opinions suggest that NPs have been "outdated" by multicore or manycore systems, which provide general purpose environments and some specialized cores. The main reasons of these negative opinions are the hard programmability of NPs, which often requires the knowledge of private microcode, or the excessive architectural limits, such as reduced memories and minimal instruction store. Our research shows that Network Processors can be appealing for different applications in networking area, and many interesting solutions can be obtained, which present very high performance, outscoring current solutions. However, the issues of hard programming and remarkable limits exist, and they could be alleviated only by providing almost a comprehensive programming environment and a proper design in terms of processing and memory resources. More e cient solutions can be surely provided, but the experience of network processors has produced an important legacy in developing packet processing engines. In this work, we have realized many devices for networking purposes based on NP platform, in order to understand the complexity of programming, the flexibility of design, the complexity of tasks that can be implemented, the maximum depth of packet processing, the performance of such devices, the real usefulness of NPs in network devices. All these features have been accurately analyzed and will be illustrated in this thesis. Many remarkable results have been obtained, which confirm the Network Processors as appealing solutions for network devices. Moreover, the research on NPs have lead us to analyze and solve more general issues, related for instance to multiprocessor systems or to processors with no big available memory. In particular, the latter issue lead us to design many interesting data structures for set representation and membership query, which are based on randomized techniques and allow for big memory savings

Pipeline Task Scheduling with Appication to Network Processors

Chip Multi-Processors (CMPs) are now available in a variety of systems and provide the opportunity for achieving high computational performance by exploiting application-level parallelism. In the communications environment, network processors (NPs), designed around CMP architectures, are generally usable in a pipelined manner. This leads to the need for static scheduling of tasks on processor pipelines. This thesis considers problems associated with determining optimal schedules for such pipelines. A collection of algorithms is presented with their utility determined by the size and other characteristics of the system. The algorithms employ heuristics, dynamic programming and statistical methods to schedule tasks derived from multiple application flows on pipelines with an arbitrary number of stages. Experimental results indicate that while the dynamic programming algorithm obtains the optimal schedules, heuristics and statistical methods obtain schedules within 10% of the optimal, 95% of the time. Examples are given to show the use of these algorithms for general pipeline/algorithm design and for use in the Network Processor environment with typical networking applications

NFComms: A synchronous communication framework for the CPU-NFP heterogeneous system

This work explores the viability of using a Network Flow Processor (NFP), developed by Netronome, as a coprocessor for the construction of a CPU-NFP heterogeneous platform in the domain of general processing. When considering heterogeneous platforms involving architectures like the NFP, the communication framework provided is typically represented as virtual network interfaces and is thus not suitable for generic communication. To enable a CPU-NFP heterogeneous platform for use in the domain of general computing, a suitable generic communication framework is required. A feasibility study for a suitable communication medium between the two candidate architectures showed that a generic framework that conforms to the mechanisms dictated by Communicating Sequential Processes is achievable. The resulting NFComms framework, which facilitates inter- and intra-architecture communication through the use of synchronous message passing, supports up to 16 unidirectional channels and includes queuing mechanisms for transparently supporting concurrent streams exceeding the channel count. The framework has a minimum latency of between 15.5 μs and 18 μs per synchronous transaction and can sustain a peak throughput of up to 30 Gbit/s. The framework also supports a runtime for interacting with the Go programming language, allowing user-space processes to subscribe channels to the framework for interacting with processes executing on the NFP. The viability of utilising a heterogeneous CPU-NFP system for use in the domain of general and network computing was explored by introducing a set of problems or applications spanning general computing, and network processing. These were implemented on the heterogeneous architecture and benchmarked against equivalent CPU-only and CPU/GPU solutions. The results recorded were used to form an opinion on the viability of using an NFP for general processing. It is the author’s opinion that, beyond very specific use cases, it appears that the NFP-400 is not currently a viable solution as a coprocessor in the field of general computing. This does not mean that the proposed framework or the concept of a heterogeneous CPU-NFP system should be discarded as such a system does have acceptable use in the fields of network and stream processing. Additionally, when comparing the recorded limitations to those seen during the early stages of general purpose GPU development, it is clear that general processing on the NFP is currently in a similar state

Simplified vector-thread architectures for flexible and efficient data-parallel accelerators

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 165-170).This thesis explores a new approach to building data-parallel accelerators that is based on simplifying the instruction set, microarchitecture, and programming methodology for a vector-thread architecture. The thesis begins by categorizing regular and irregular data-level parallelism (DLP), before presenting several architectural design patterns for data-parallel accelerators including the multiple-instruction multiple-data (MIMD) pattern, the vector single-instruction multiple-data (vector-SIMD) pattern, the single-instruction multiple-thread (SIMT) pattern, and the vector-thread (VT) pattern. Our recently proposed VT pattern includes many control threads that each manage their own array of microthreads. The control thread uses vector memory instructions to efficiently move data and vector fetch instructions to broadcast scalar instructions to all microthreads. These vector mechanisms are complemented by the ability for each microthread to direct its own control flow. In this thesis, I introduce various techniques for building simplified instances of the VT pattern. I propose unifying the VT control-thread and microthread scalar instruction sets to simplify the microarchitecture and programming methodology. I propose a new single-lane VT microarchitecture based on minimal changes to the vector-SIMD pattern.(cont.) Single-lane cores are simpler to implement than multi-lane cores and can achieve similar energy efficiency. This new microarchitecture uses control processor embedding to mitigate the area overhead of single-lane cores, and uses vector fragments to more efficiently handle both regular and irregular DLP as compared to previous VT architectures. I also propose an explicitly data-parallel VT programming methodology that is based on a slightly modified scalar compiler. This methodology is easier to use than assembly programming, yet simpler to implement than an automatically vectorizing compiler. To evaluate these ideas, we have begun implementing the Maven data-parallel accelerator. This thesis compares a simplified Maven VT core to MIMD, vector-SIMD, and SIMT cores. We have implemented these cores with an ASIC methodology, and I use the resulting gate-level models to evaluate the area, performance, and energy of several compiled microbenchmarks. This work is the first detailed quantitative comparison of the VT pattern to other patterns. My results suggest that future data-parallel accelerators based on simplified VT architectures should be able to combine the energy efficiency of vector-SIMD accelerators with the flexibility of MIMD accelerators.by Christopher Francis Batten.Ph.D