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Forthcoming technologies hold the promise of a significant increase in integration density, performance and functionality. However, a dramatic change in microprocessor's reliability is also expected. Developing mechanisms for early and accurate reliability estimation will save significant design effort, resources and consequently will positively impact product's timeto-market (TTM). In this paper, we propose a versatile architecture-level fault injection framework, built on top of a state-of-the-art x86 microprocessor simulator, for thorough and fast characterization of a wide range of hardware components with respect to various fault models.

Blockchain technology has become extremely popular, during the last decade, mainly due to the successful application in the cryptocurrency domain. Following the explosion of Bitcoin and other cryptocurrencies, blockchain solutions are being deployed in almost every aspect of transactional operations as a means to safely exchange digital assets between non-trusted parties. At the heart of every blockchain deployment is the consensus protocol, which maintains the consistency of the blockchain upon satisfying incoming transactions. Although many consensus protocols have been recently introduced, the most prevalent is Proof-of-Work, which scales the blockchain globally by converting the consensus problem to a competition based on cryptographic hash functions; a process called "mining". The Proof-of-Work consensus protocol employs memoryhard algorithms in order to counteract ASIC or FPGA mining that may compromise the decentralization and democratization of the blockchain. Unfortunately, this leads to increased power consumption and scalability challenges since numerous processing units such as GPUs, FPGAs, and ASICs, are required to satisfy the ever-increasing operational requirements of blockchain deployments. In this paper, we perform an in-depth performance analysis and characterization of the most common memory-hard PoW algorithms running on NVIDIA GPUs. Motivated by our experimental findings, we apply a series of optimizations on Ethash algorithm, the consensus protocol of the Ethereum blockchain. The implemented optimizations accelerate performance by 14% and improve energy efficiency by 10% when executing on three NVIDIA GPUs. As a result, the optimized Ethash algorithm outperformed its fastest commercial implementation.

International audienceAdvanced computing systems realized in forthcoming technologies hold the promise of a significant increase of computational capabilities. However, the same path that is leading technologies toward these remarkable achievements is also making electronic devices increasingly unreliable. Developing new methods to evaluate the reliability of these systems in an early design stage has the potential to save costs, produce optimized designs and have a positive impact on the product time-to-market

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Extending current Virtual Machine implementations to new Instruction Set Architectures entails a significant programming and debugging effort. Meta-circular VMs add another level of complexity towards this aim since they have to compile themselves with the same compiler that is being extended. Therefore, having low-level debugging tools is of vital importance in decreasing development time and bugs introduced. In this paper we describe our experiences in extending Maxine VM to the ARMv7 architecture. During that process, we developed a QEMU-based toolchain which enables us to debug a wide range of VM features in an automated way. The presented toolchain has been integrated with the JUNIT testing framework of Maxine VM and is capable of executing from simple assembly instructions to fully JIT compiled code. Furthermore, it is fully open-sourced and can be adapted to any other VMs seamlessly. Finally, we describe a compiler-assisted methodology that helps us identify, at runtime, faulty methods that generate no stack traces, in an automatic and fast manner. CCS Concepts • Software and its engineering → Justin-time compilers; Software testing and debugging;