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Achieving Green AI with Energy-Efficient Deep Learning Using Neuromorphic Computing

Achieving Green AI with Energy-Efficient Deep Learning Using Neuromorphic Computing
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National university of singaporeSingapore generalHaizhou liWenyu jiangWeiyun yauTao luoZhixian chenNeural networksSchool of computing soAssociation for computing machineryVideo technologyAgency for scienceInstitute of high performance computingInstitute of microelectronicsDigital libraryAcm inc

Arcelik s developers boosted with advanced capabilities of Open AIGPT Models

ISTANBUL, June 9, 2023 /PRNewswire/ Arcelik, one of Europe's leading home appliances companies, has today announced the launch of the 'Arcelik Developers' AI Platform', a new web application designed to enhance the efficiency and capabilities of its developers in coding by utilizing multiple features through artificial intelligence, such as code generation, error detection, code optimization, and automated testing. Available to developers across the organisation, the platform has been built to integrate seamlessly with OpenAI GPT model, strengthening the security and confidentiality of intellectual property across the global organization through the incredible power of AI. Utku Bar Pazar, Arcelik Chief Strategy and Digital Officer Arcelik Developers' AI Platform marks a promising roadmap for the company which boasts a global workforce of 40,000 employees across 12 brands and over 100 countries. In opening up the Platform, Arcelik hopes to revolutionize the way dev

Prnewswire arcelikArcelik developerBar pazarArcelik chief strategyUtku bar pazarChief strategyDigital officerArcelik developer platformJune 9023 prnewswire arcelikNe of europe 39s leading home appliances companiesAs today announced the launch of 39 arcelik developers ai platformA new web application designed to enhance the efficiency and capabilities of its developers in coding by utilizing multiple features through artificial intelligenceUch as code generationError detectionCode optimization

MemHC Optimizes Many-Body Correlation Function Vital to Physics Computing

MemHC Optimizes Many-Body Correlation Function Vital to Physics Computing
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Jie chenQihan wangRobertg edwardsZhen pengBin renManagement frameworkAccelerating many body correlationCode optimization

Reducing code size with LLVM Machine Outliner on 32-bit Arm targets

Reducing code size with LLVM Machine Outliner on 32-bit Arm targets Yvan Roux | 9 mins read With the upcoming release of LLVM 12.0.0, 32-bit Arm targets have gained the full support of the Machine Outliner code size optimization for Arm and Thumb-2 instruction sets. The expected code size gain provided by this optimization is around 5% on average (you can jump straight to the results part for more details). It is not turned on by default (see How to use it section) but our goal is to have it enabled under -Oz for all Arm cores inside LLVM 13.0.0. Function outlining is a compilation process which consists of replacing a chunk of consecutive statements with a call to a new function containing those statements. In a nutshell, it is the inverse of the well known inlining optimization. It is used in different areas of compilation to achieve various goals such as code refactoring or kernel extraction in source to source compilers, shrinking large functions to reduce compile time in

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