Blockchains promise to make online services more fault tolerant because they are replicated on a distributed system of nodes. Their nodes typically run different implementations of the same protocol across different geo-distributed regions, making the protocol supposedly tolerant to various failures including isolated crashes, transient failures, network partitions or attacks. Unfortunately, their fault tolerance has never been compared.

This paper introduces Carbon, a high-throughput system enabling asynchronous (safe) and consensus-free (efficient) payments and votes within a dynamic set of clients. Carbon is operated by a dynamic set of validators that may be reconfigured asynchronously, offering its clients eclipse resistance as well as lightweight bootstrap. Carbon offers clients the ability to select validators by voting them in and out of the system thanks to its novel asynchronous and stake-less voting mechanism. Carbon relies on an asynchronous and deterministic implementation of Byzantine reliable broadcast that uniquely leverages a permissionless set of untrusted servers, brokers, to slash the cost of client authentication inherent to Byzantine fault tolerant systems. Carbon is able to sustain a throughput of one million payments per second in a geo-distributed environment, outperforming the state of the art by three orders of magnitude with equivalent latencies.

With the recent advent of blockchains, we have witnessed a plethora of blockchain proposals. These proposals range from using work to using time, storage or stake in order to select blocks to be appended to the chain. As a drawback it makes it difficult for the application developer to choose the right blockchain to support their applications. In particular, the scalability and performance one can obtain from a specific blockchain is typically unknown. The claimed results are often obtained in isolation by the developers of the blockchain themselves. The experimental conditions corresponding to these results are generally missing and the lack of details make these results irreproducible.

We present SAZyzz, a leader-based Byzantine Fault Tolerant consensus protocol for partially synchronous networks. SAZyzz exhibits a better performance/scalability compared to the state-of-the-art leader-based BFT consensus protocols. It is built on top of AZyzzyva and has adopted a tree-based communication model which enables it to enhance the scalability of AZyzzyva. Additionally, SAZyzz reduces the communication complexity toO(logN) in two paths of the protocol. However, the tree-based topology has been argued that has a shortcoming when used in designing BFT consensus protocols. This refers to the strong assumption that all the internal nodes of the tree are honest, which leads to a trade-off between tolerating Byzantine faults and better performance and scalability. This paper shows that, with the current technological infrastructures available for industrial systems, such as Trusted Execution Environment (TEE) and Public Key Infrastructure (PKI), this assumption is realistic. SAZyzz comprises of fast-path and backup-path, each of which has two modes:simple modeandscalable mode. To demonstrate the efficiency and feasibility of SAZyzz's adoption for blockchain systems, we designed and implemented the ZyConChain blockchain system based on SAZyzz. The evaluation results show that SAZyzz can significantly improve the performance/scalability of blockchain systems.

Understanding the performance of a multi-threaded application is difficult. The threads interfere when they access the same shared resource, which slows down their execution. Unfortunately, current profiling tools report the hardware components or the synchronization primitives that saturate, but they cannot tell if the saturation is the cause of a performance bottleneck. In this paper, we propose a holistic metric able to pinpoint the blocks of code that suffer interference the most, regardless of the interference cause. Our metric uses performance variation as a universal indicator of interference problems. With an evaluation of 27 applications we show that our metric can identify interference problems caused by six different kinds of interference in nine applications. We are able to easily remove seven of the bottlenecks, which leads to a performance improvement of up to nine times.

While virtualization only introduces a small overhead on machines with few cores, this is not the case on larger ones. Most of the overhead on the latter machines is caused by the Non-Uniform Memory Access (NUMA) architecture they are using. In order to reduce this overhead, this paper shows how NUMA placement heuristics can be implemented inside Xen. With an evaluation of 29 applications on a 48-core machine, we show that the NUMA placement heuristics can multiply the performance of 9 applications by more than 2.