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Towards a Methodology and Framework for AI Sustainability Metrics 23

Towards a Methodology and Framework for AI Sustainability Me...

引用

2nd acm Workshop on Sustainable Computer systems (acm HotCarbon)

作者： Eilam, Tamar Bello-Maldonado, Pedro D. Bhattacharjee, Bishwaranjan Costa, Carlos Lee, Eun K. Tantawi, Asser IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA

ISBN: (纸本)9798400702426

Recently, we are witnessing truly groundbreaking achievements using AI models, such as the much talked about generative large language models, the broader area of foundation models, and the wide range of applications with a tremendous potential to accelerate scientific discovery, and enhance productivity. AI models and their use are growing at a super-linear pace. Inference jobs are measured by the trillions, and model parameters by the billions. This scaling up comes with a tremendous environmental cost, associated with every aspect of models' life cycle: data preparation, pre-training, and post deployment re-training, inference, and, the embodied emission of the systems used to support the execution. There is an urgent need for the community to come together and conduct a meaningful conversation about the environmental cost of AI. To do that, we ought to develop an agreed upon set of metrics, methodology, and framework to quantify AI's sustainability cost in a holistic and complete fashion. In this paper, we propose unified AI Sustainability metrics that can help foster a sustainability mind-set and enable analysis, and strategy setting. To do that, we build on and extend the data center sustainability metrics, defined in [19], by introducing (for the first time to our knowledge) the concept of embodied product emission (EPC) to capture the creation cost of software assets, such as software platforms, models, and data-sets. We then use this new concept to expand the job sustainability cost metrics (JCS and ASC) offered in [19] to factor in the context of the execution of jobs, such as a platform as-a-service, or a model serving inference jobs. The result is applicable to any data center job, not just for AI, and contributes towards accuracy and completeness. We then show how to apply this approach to AI, with a particular focus on the entire life cycle, including all phases of the life cycle, as well as the provenance of models, where one model is used (distilled)

关键词： green AI foundation models sustainable AI sustainable computing

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CheckMate: LLM-Powered Approximate Intermittent computing 25

CheckMate: LLM-Powered Approximate Intermittent Computing

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proceedings of the 23rd acm Conference on Embedded Networked Sensor systems

作者： Abdur-rahman Ibrahim Sayyid-Ali Abdul Rafay Muhammad Abdullah Soomro Muhammad Hamad Alizai Naveed Anwar Bhatti Lahore University of Management Sciences Lahore Pakistan

ISBN: (纸本)9798400714795

Batteryless IoT systems face energy constraints exacerbated by checkpointing overhead. Approximate computing offers solutions but demands manual expertise, limiting scalability. This paper presents CheckMate, an automated framework leveraging LLMs for context-aware code approximations. CheckMate integrates validation of LLM-generated approximations to ensure correct execution and employs Bayesian optimization to fine-tune approximation parameters autonomously, eliminating the need for developer input. Tested across six IoT applications, it reduces power cycles by up to 60% with an accuracy loss of just 8%, outperforming semi-automated tools like ACCEPT in speedup and accuracy. CheckMate's results establish it as a robust, user-friendly tool and a foundational step toward automated approximation frameworks for intermittent computing.

关键词： intermittent computing

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proceedings of PDSW 2020: IEEE/acm 5th International Parallel Data systems Workshop, Held in conjunction with SC 2020: The International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of PDSW 2020: IEEE/ACM 5th International Paralle...

引用

5th IEEE/acm International Parallel Data systems Workshop, PDSW 2020

ISBN: (纸本)9781665415941

The proceedings contain 8 papers. The topics discussed include: keeping it real: why HPC data services don’t achieve I/O microbenchmark performance;towards on-demand I/O forwarding in HPC platforms;gauge: an interactive data-driven visualization tool for HPC application I/O performance analysis;fractional-overlap declustered parity: evaluating reliability for storage systems;GPU direct I/O with HDF5;emulating I/O behavior in scientific workflows on high performance computing systems;Pangeo benchmarking analysis: object storage vs. POSIX file system;and fingerprinting the checker policies of parallel file systems.

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A Quantitative Approach for Adopting Disaggregated Memory in HPC systems 23

A Quantitative Approach for Adopting Disaggregated Memory in...

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2023 International Conference for High Performance computing, Networking, Storage and analysis, SC 2023

作者： Wahlgren, Jacob Schieffer, Gabin Gokhale, Maya Peng, Ivy KTH Royal Institute of Technology Stockholm Sweden Lawrence Livermore National Laboratory Livermore United States

ISBN: (纸本)9798400701092

Memory disaggregation has recently been adopted in data centers to improve resource utilization, motivated by cost and sustainability. Recent studies on large-scale HPC facilities have also highlighted memory underutilization. A promising and non-disruptive option for memory disaggregation is rack-scale memory pooling, where node-local memory is supplemented by shared memory pools. This work outlines the prospects and requirements for adoption and clarifies several misconceptions. We propose a quantitative method for dissecting application requirements on the memory system from the top down in three levels, moving from general, to multi-tier memory systems, and then to memory pooling. We provide a multi-level profiling tool and LBench to facilitate the quantitative approach. We evaluate a set of representative HPC workloads on an emulated platform. Our results show that prefetching activities can significantly influence memory traffic profiles. Interference in memory pooling has varied impacts on applications, depending on their access ratios to memory tiers and arithmetic intensities. Finally, in two case studies, we show the benefits of our findings at the application and system levels, achieving 50% reduction in remote access and 13% speedup in BFS, and reducing performance variation of co-located workloads in interference-aware job scheduling. © 2023 acm.

关键词： HPC system disaggregated memory multi-tier memory

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Reliability analysis of Memristive Reservoir computing Architecture 23

Reliability Analysis of Memristive Reservoir Computing Archi...

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33rd Great Lakes Symposium on VLSI (GLSVLSI)

作者： Rathore, Manu Febbo, Rocco Foshie, Adam Tushar, S. N. B. Das, Hritom Rose, Garrett S. Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9798400701252

Neuromorphic computing systems have emerged as powerful computation tools in the field of object recognition and control systems. However, training these systems, which are usually characterized by recurrent connectivity, requires abundant computational resources: memory, computation, data, and time. Reservoir computing (RC) framework reduces this high computational training cost by focusing the training effort on only a small subset of connections thus allowing these systems to be amenable to hardware implementation. Using memristors to construct these reservoir computers reduce the area/power consumption even further. However, the inherent variability of memristors poses specific challenges. Here, we conduct an in-depth reliability analysis of challenges posed by HfO2 memristors, including cycle-to-cycle variability, read/write noise, and conductance drift in the context of RC hardware. We also explore plasticity mechanisms such as Spike-Timing Dependent Plasticity (STDP) within the scope of the spiking recurrent neural networks (SRNN) reservoir and their impact on memristor conductance drift (MCD). We present a chaotic time series prediction task applied to a Python model of the constrained hardware design achieving very low Normalized Root Mean Square Error (NRMSE) of 2 x 10(-3). The analog neuron and memristive synapse circuits employed for constructing the SRNN are simulated in Cadence Spectre and the energy consumption for the Mackey-Glass (MG) time-series prediction task was found to be approximately 90 nJ.

关键词： Neuromorphic Reservoir computing Liquid State Machine Echo State Networks Spiking Recurrent Neural Network Memristor ReRAM DPE STDP Device Variability Conductance drift

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Envisioning Narrative Intelligence: A Creative Visual Storytelling Anthology 23

Envisioning Narrative Intelligence: A Creative Visual Storyt...

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CHI conference on Human Factors in computing systems (CHI)

作者： Halperin, Brett A. Lukin, Stephanie M. Univ Washington Human Centered Design & Engn Seattle WA 98195 USA DEVCOM Army Res Lab Playa Vista CA USA

ISBN: (纸本)9781450394215

In this paper, we collect an anthology of 100 visual stories from authors who participated in our systematic creative process of improvised story-building based on image sequences. Following close reading and thematic analysis of our anthology, we present five themes that characterize the variations found in this creative visual storytelling process: (1) Narrating What is in Vision vs. Envisioning;(2) Dynamically Characterizing Entities/Objects;(3) Sensing Experiential Information About the Scenery;(4) Modulating the Mood;(5) Encoding Narrative Biases. In understanding the varied ways that people derive stories from images, we offer considerations for collecting story-driven training data to inform automatic story generation. In correspondence with each theme, we envision narrative intelligence criteria for computational visual storytelling as: creative, reliable, expressive, grounded, and responsible. From these criteria, we discuss how to foreground creative expression, account for biases, and operate in the bounds of visual storyworlds.

关键词： Bias Creativity Crowdsourcing Narrative Intelligence Narrative systems Story Generation Storytelling Visual Storytelling

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Seeking Inspiration through Human-LLM Interaction 25

Seeking Inspiration through Human-LLM Interaction

引用

2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Lin, Xinrui Huang, Heyan Huang, Kaihuang Shu, Xin Vines, John Beijing Institute of Technology Beijing China University of Edinburgh Edinburgh United Kingdom Oppo Shenzhen China Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400713941

Large language model (LLM) systems have been shown to stimulate creative thinking among creators, yet empirical research on whether users can seek inspiration in their everyday lives through these technologies is lacking. This paper explores which attributes of LLMs influence inspiration-seeking processes. Focusing on use cases of travel, cooking, and self-care, we interviewed 20 participants as they explored scenarios of these use cases using LLMs. Thematic analysis revealed that the vast data of LLMs inspires users with unexpected ideas, many of which were highly personalized, and inspired participants towards being motivated to act. Participants were also sensitive to the deficiencies of LLMs, and noted how ethical issues associated with these technologies could negatively impact them applying inspirational ideas into practice. We discuss the behavioral patterns of users actively seeking inspiration via LLMs, and provide design opportunities for LLMs that make the inspiration-seeking process more human-centric. © 2025 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Inspiration Large language models Qualitative analysis

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Practical Runtime Instrumentation of Software Languages: The Case of SCIHOOK 16

Practical Runtime Instrumentation of Software Languages: The...

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16th acm SIGPLAN International Conference on Software Language Engineering (SLE) as part of SPLASH Conference

作者： Leroy, Dorian Combemale, Benoit Lelandais, Benoit Oudot, Marie-Pierre CEA DAM DIF F-91297 Arpajon France Univ Paris Saclay CEA LIHPC DAMDIF F-91297 Arpajon France Univ Rennes Rennes France

ISBN: (纸本)9798400703966

Software languages have pros and cons, and are usually chosen accordingly. In this context, it is common to involve different languages in the development of complex systems, each one specifically tailored for a given concern. However, these languages create de facto silos, and offer little support for interoperability with other languages, be it statically or at runtime. In this paper, we report on our experiment on extracting a relevant behavioral interface from an existing language, and using it to enable interoperability at runtime. In particular, we present a systematic approach to define the behavioral interface and we discuss the expertise required to define it. We illustrate our work on the case study of SCIHOOK, a C++ library enabling the runtime instrumentation of scientific software in Python. We present how the proposed approach, combined with SciHook, enables interoperability between Python and a domain-specific language dedicated to numerical analysis, namely NABLAB, and discuss overhead at runtime.

关键词： language interoperability instrumentation C plus Python domain-specific languages scientific computing

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Automatically Localizing Dynamic Code Generation Bugs in JIT Compiler Back-End 2023

Automatically Localizing Dynamic Code Generation Bugs in JIT...

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32nd acm SIGPLAN International Conference on Compiler Construction (CC)

作者： Lim, HeuiChan Debray, Saumya Univ Arizona Dept Comp Sci Tucson AZ 85721 USA

ISBN: (纸本)9798400700880

Just-in-Time (JIT) compilers are ubiquitous in modern computing systems and are used in a wide variety of software. Dynamic code generation bugs, where the JIT compiler silently emits incorrect code, can result in exploitable vulnerabilities. They, therefore, pose serious security concerns and make quick mitigation essential. However, due to the size and complexity of JIT compilers, quickly locating and fixing bugs is often challenging. In addition, the unique characteristics of JIT compilers make existing bug localization approaches inapplicable. Therefore, this paper proposes a new approach to automatic bug localization, explicitly targeting the JIT compiler back-end. The approach is based on explicitly modeling architecture-independent back-end representation and architecture-specific code-generation. Experiments using a prototype implementation on a widely used JIT compiler (Turbofan) indicate that it can successfully localize dynamic code generation bugs in the back-end with high accuracy.

关键词： JIT Compiler Back-End Dynamic Program analysis Dynamic Code Generation Automatic Bug Localization

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The Halting problem: Video analysis of self-driving cars in traffic 23

The Halting problem: Video analysis of self-driving cars in ...

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CHI conference on Human Factors in computing systems (CHI)

作者： Brown, Barry Broth, Mathias Vinkhuyzen, Erik Univ Copenhagen Copenhagen Denmark Stockholm Univ Stockholm Sweden Linkopings Univ Inst Kultur Samhalle IKOS Linkoping Sweden Kings Coll London Work Interact & Technol Res Grp London England

ISBN: (纸本)9781450394215

Using publicly uploaded videos of the Waymo and Tesla FSD self-driving cars, this paper documents how self-driving vehicles still struggle with some basics of road interaction. To drive safely self-driving cars need to interact in traffic with other road users. Yet traffic is a complex, long established social domain. We focus on one core element of road interaction: when road users yield for each other. Yielding - slowing down for others in traffic - involves communication between different road users to decide who will 'go' and who will 'yield'. Videos of the Waymo and Tesla FSD self-driving cars show how these systems fail to both yield for others, as well as failing to go when yielded to. In discussion, we explore how these 'problems' illustrate both the complexity of designing for road interaction, but also how the space of physical machine/human social interactions more broadly can be designed for.

关键词： Roads and streets

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