Efficient intermittent computing with differential checkpointing

Ahmed, Saad; Bhatti, Naveed Anwar; Alizai, Muhammad Hamad; Siddiqui, Junaid Haroon; Mottola, Luca

doi:10.1145/3316482.3326357

Cited by 44 publications

(28 citation statements)

References 31 publications

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“…A very recent example to such a study uses checkpointing in persisting distributed legacy in memory software by the introduction of a persistent memory based tool [27]. Another recent study in non volatile memory systems uses differential checkpointing to leverage energy efficiency [28]. Even though state machines are not explicitly used in this study, a recent application of differential checkpointing is presented.…”

Section: Related Workmentioning

confidence: 99%

Distributed Application Checkpointing for Replicated State Machines

Celikel

Ovatman

2021

SCPE

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Application checkpointing is a widely used recovery mechanism that consists of saving an application's state periodically to be used in case of a failure. In this study we investigate the utilisation of distributed checkpointing for replicated state machines. Conventionally, for replicated state machines, checkpointing information is stored in a replicated way in each of the replicas or separately in a single instance. Applying distributed checkpointing provides a means to adjust the level of fault tolerance of the checkpointing approach by giving away from recovery time. We use a local cluster and cloud environment to examine the effects of distributed checkpointing in a simple state machine example and compare the results with conventional approaches. As expected, distributed checkpointing gains from memory consumption and utilise different levels of fault tolerance while performing worse in terms of recovery time.

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Section: Related Workmentioning

confidence: 99%

Distributed Application Checkpointing for Replicated State Machines

Celikel

Ovatman

2021

SCPE

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“…Hibernus++ remains a key work in this field, with only a few authors re-visiting reactive approaches [22] [23]. The key benefit of these reactive systems is that they place little-to-no burden on the programmer, instead allowing standard embedded programs to be compiled and run.…”

Section: Background and Related Workmentioning

confidence: 99%

Improving the Forward Progress of Transient Systems

Daulby

Savanth

Merrett

et al. 2021

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Emerging applications for Internet of Things devices demand smaller mass, size and cost whilst increasing capability and reliability. Energy harvesting can provide power to these ultra-constrained devices, but introduces unreliability, unpredictability and intermittency. Schemes for wireless sensors without batteries or supercapacitors overcome intermittency through saving system state into non-volatile memory before the supply drops below the minimum operating voltage, termed transient or intermittent computing. However, this introduces significant time and energy overheads. This paper presents two schemes that significantly reduce these overheads: entering a sleep mode to avoid saving state and utilising direct memory access (DMA) when state saves are required. Time and energy previously wasted on state saves can instead be used to perform useful computation, termed "forward progress". We practically validate the proposed approaches across a range of energy sources and IoT benchmarks and demonstrate up to 46.8% and 40.3% increase in forward progress and up to 91.1% and 85.6% reduction in overheads for each scheme respectively.

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“…ThyNVM [38] reduces the program execution stalls that are necessary for creating checkpoints by increasing the stored metadata to allow variable granularity (i.e., cache block or page) checkpointing. DICE [1] is a differential checkpoint software plugin that is compatible with several existing checkpoint techniques. It is designed for energy-ambient embedded devices that perform intermittent computing.…”

Section: Related Workmentioning

confidence: 99%

Compiler-support for Critical Data Persistence in NVM

Elkhouly

Alshboul

Hayashi

et al. 2019

ACM Trans. Archit. Code Optim.

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Non-volatile Main Memories (NVMs) offer a promising way to preserve data persistence and enable computation recovery in case of failure. While the use of NVMs can significantly reduce the overhead of failure recovery, which is the case with High-Performance Computing (HPC) kernels, rewriting existing programs or writing new applications for NVMs is non-trivial. In this article, we present a compiler-support that automatically inserts complex instructions into kernels to achieve NVM data-persistence based on a simple programmer directive. Unlike checkpointing techniques that store the whole system state, our technique only persists user-designated objects as well as some parameters required for safe recovery such as loop induction variables. Also, our technique can reduce the number of data transfer operations, because our compiler coalesces consecutive memory-persisting operations into a single memory transaction per cache line when possible. Our compiler-support is implemented in the LLVM tool-chain and introduces the necessary modifications to loop-intensive computational kernels (e.g., TMM, LU, Gauss, and FFT) to force data persistence. The experiments show that our proposed compiler-support outperforms the most recent checkpointing techniques while its performance overheads are insignificant. CCS Concepts: • Software and its engineering → Source code generation; Runtime environments; Main memory; • Hardware → Emerging languages and compilers;

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Efficient intermittent computing with differential checkpointing

Cited by 44 publications

References 31 publications

Distributed Application Checkpointing for Replicated State Machines

Distributed Application Checkpointing for Replicated State Machines

Improving the Forward Progress of Transient Systems

Compiler-support for Critical Data Persistence in NVM

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