Academic literature on the topic 'Tensor Compilers'

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Journal articles on the topic "Tensor Compilers"

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Deeds, Kyle, Willow Ahrens, Magdalena Balazinska, and Dan Suciu. "Galley: Modern Query Optimization for Sparse Tensor Programs." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–24. https://doi.org/10.1145/3725301.

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The tensor programming abstraction is a foundational paradigm which allows users to write high performance programs via a high-level imperative interface. Recent work on sparse tensor compilers has extended this paradigm to sparse tensors (i.e., tensors where most entries are not explicitly represented). With these systems, users define the semantics of the program and the algorithmic decisions in a concise language that can be compiled to efficient low-level code. However, these systems still require users to make complex decisions about program structure and memory layouts to write efficient
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Liu, Peiming, Alexander J. Root, Anlun Xu, Yinying Li, Fredrik Kjolstad, and Aart J. C. Bik. "Compiler Support for Sparse Tensor Convolutions." Proceedings of the ACM on Programming Languages 8, OOPSLA2 (2024): 275–303. http://dx.doi.org/10.1145/3689721.

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This paper extends prior work on sparse tensor algebra compilers to generate asymptotically efficient code for tensor expressions with affine subscript expressions. Our technique enables compiler support for a wide range of sparse computations, including sparse convolutions and pooling that are widely used in ML and graphics applications. We propose an approach that gradually rewrites compound subscript expressions to simple subscript expressions with loops that exploit the sparsity pattern of the input sparse tensors. As a result, the time complexity of the generated kernels is bounded by the
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Liu, Jiawei, Yuxiang Wei, Sen Yang, Yinlin Deng, and Lingming Zhang. "Coverage-guided tensor compiler fuzzing with joint IR-pass mutation." Proceedings of the ACM on Programming Languages 6, OOPSLA1 (2022): 1–26. http://dx.doi.org/10.1145/3527317.

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In the past decade, Deep Learning (DL) systems have been widely deployed in various application domains to facilitate our daily life, e.g., natural language processing, healthcare, activity recognition, and autonomous driving. Meanwhile, it is extremely challenging to ensure the correctness of DL systems (e.g., due to their intrinsic nondeterminism), and bugs in DL systems can cause serious consequences and may even threaten human lives. In the literature, researchers have explored various techniques to test, analyze, and verify DL models, since their quality directly affects the corresponding
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Dias, Adhitha, Logan Anderson, Kirshanthan Sundararajah, Artem Pelenitsyn, and Milind Kulkarni. "SparseAuto: An Auto-scheduler for Sparse Tensor Computations using Recursive Loop Nest Restructuring." Proceedings of the ACM on Programming Languages 8, OOPSLA2 (2024): 527–56. http://dx.doi.org/10.1145/3689730.

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Automated code generation and performance enhancements for sparse tensor algebra have become essential in many real-world applications, such as quantum computing, physical simulations, computational chemistry, and machine learning. General sparse tensor algebra compilers are not always versatile enough to generate asymptotically optimal code for sparse tensor contractions. This paper shows how to generate asymptotically better schedules for complex sparse tensor expressions using kernel fission and fusion. We present generalized loop restructuring transformations to reduce asymptotic time comp
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Zhou, Chijin, Bingzhou Qian, Gwihwan Go, Quan Zhang, Shanshan Li, and Yu Jiang. "PolyJuice: Detecting Mis-compilation Bugs in Tensor Compilers with Equality Saturation Based Rewriting." Proceedings of the ACM on Programming Languages 8, OOPSLA2 (2024): 1309–35. http://dx.doi.org/10.1145/3689757.

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Tensor compilers are essential for deploying deep learning applications across various hardware platforms. While powerful, they are inherently complex and present significant challenges in ensuring correctness. This paper introduces PolyJuice, an automatic detection tool for identifying mis-compilation bugs in tensor compilers. Its basic idea is to construct semantically-equivalent computation graphs to validate the correctness of tensor compilers. The main challenge is to construct equivalent graphs capable of efficiently exploring the diverse optimization logic during compilation. We approac
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Krastev, Aleksandar, Nikola Samardzic, Simon Langowski, Srinivas Devadas, and Daniel Sanchez. "A Tensor Compiler with Automatic Data Packing for Simple and Efficient Fully Homomorphic Encryption." Proceedings of the ACM on Programming Languages 8, PLDI (2024): 126–50. http://dx.doi.org/10.1145/3656382.

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Fully Homomorphic Encryption (FHE) enables computing on encrypted data, letting clients securely offload computation to untrusted servers. While enticing, FHE has two key challenges that limit its applicability: it has high performance overheads (10,000× over unencrypted computation) and it is extremely hard to program. Recent hardware accelerators and algorithmic improvements have reduced FHE’s overheads and enabled large applications to run under FHE. These large applications exacerbate FHE’s programmability challenges. Writing FHE programs directly is hard because FHE schemes expose a restr
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Noor, Abdul Rafae, Dhruv Baronia, Akash Kothari, Muchen Xu, Charith Mendis, and Vikram S. Adve. "MISAAL: Synthesis-Based Automatic Generation of Efficient and Retargetable Semantics-Driven Optimizations." Proceedings of the ACM on Programming Languages 9, PLDI (2025): 1269–92. https://doi.org/10.1145/3729301.

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Using program synthesis to select instructions for and optimize input programs is receiving increasing attention. However, existing synthesis-based compilers are faced by two major challenges that prohibit the deployment of program synthesis in production compilers: exorbitantly long synthesis times spanning several minutes and hours; and scalability issues that prevent synthesis of complex modern compute and data swizzle instructions, which have been found to maximize performance of modern tensor and stencil workloads. This paper proposes MISAAL, a synthesis-based compiler that employs a nove
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Chou, Stephen, Fredrik Kjolstad, and Saman Amarasinghe. "Format abstraction for sparse tensor algebra compilers." Proceedings of the ACM on Programming Languages 2, OOPSLA (2018): 1–30. http://dx.doi.org/10.1145/3276493.

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Clément, Basile, and Albert Cohen. "End-to-end translation validation for the halide language." Proceedings of the ACM on Programming Languages 6, OOPSLA1 (2022): 1–30. http://dx.doi.org/10.1145/3527328.

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This paper considers the correctness of domain-specific compilers for tensor programming languages through the study of Halide, a popular representative. It describes a translation validation algorithm for affine Halide specifications, independently of the scheduling language. The algorithm relies on “prophetic” annotations added by the compiler to the generated array assignments. The annotations provide a refinement mapping from assignments in the generated code to the tensor definitions from the specification. Our implementation leverages an affine solver and a general SMT solver, and scales
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Arora, Jai, Sirui Lu, Devansh Jain, et al. "TensorRight: Automated Verification of Tensor Graph Rewrites." Proceedings of the ACM on Programming Languages 9, POPL (2025): 832–63. https://doi.org/10.1145/3704865.

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Tensor compilers, essential for generating efficient code for deep learning models across various applications, employ tensor graph rewrites as one of the key optimizations. These rewrites optimize tensor computational graphs with the expectation of preserving semantics for tensors of arbitrary rank and size. Despite this expectation, to the best of our knowledge, there does not exist a fully automated verification system to prove the soundness of these rewrites for tensors of arbitrary rank and size. Previous works, while successful in verifying rewrites with tensors of concrete rank, do not
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Dissertations / Theses on the topic "Tensor Compilers"

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Chou, Stephen S. M. Massachusetts Institute of Technology. "Unfield sparse formats for tensor algebra compilers." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115625.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 99-105).<br>Tensor algebra is a powerful tool for computing on multidimensional data and has applications in many fields. Practical applications often deal with tensors that are sparse, and there exists a wide variety of format
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Gao, Xiaoyang. "Integrated compiler optimizations for tensor contractions." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1198874631.

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Mueller, Suzanne A. "Sparse tensor transpositions in the tensor algebra compiler." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129919.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020<br>Cataloged from student-submitted PDF of thesis.<br>Includes bibliographical references (pages 89-90).<br>The current state of the art for transposing sparse tensors involves converting the sparse tensor into a list of coordinates, sorting the list of coordinates and finally packing the list of coordinates into the desired sparse tensor format. This thesis explores the potential for faster methodologies. Its main contributions are an algorithm that exploits partia
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Noyola, Patricio. "A Tensor Algebra Compiler library interface and runtime." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123041.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 65-66 ).<br>Tensor algebra is a powerful tool for computing on multidimensional data and has applications in many fields. The number of possible tensor operations is infinite, so it is impossible to manually implement all of t
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Katel, Naveep Kumar. "High Performance GPU Tensor Core Code Generation for Matmul using MLIR." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5594.

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State of the art in high-performance deep learning is primarily driven by highly tuned libraries. These libraries are often hand-optimized and tuned by expert programmers using low-level abstractions with significant effort. A lot of the effort may have to be repeated for similar hardware and future ones. This process is thus not modular or reusable to the same extent that compiler infrastructures like LLVM are. Manual optimization does not typically use a standard intermediate representation (IR) or transformations and passes on such IRs, although the optimizations performed can be encoded as
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Books on the topic "Tensor Compilers"

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Hunt, John. Tenors in a lyric tradition: Peter Anders, Walther Ludwig, Fritz Wunderlich : discographies compiled by John Hunt with valuable assistance from Clifford Elkin. J. Hunt, 1996.

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The catechisms of the Methodist Church of Canada: Compiled and published for the use of the families and schools connected with that body : no. 1, for children of tender years .. S.F. Huestis, 1987.

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Book chapters on the topic "Tensor Compilers"

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Jolly, John, Priya Goyal, Vishal Sahoo, Hans Johansen, and Mary Hall. "Tensor Iterators for Flexible High-Performance Tensor Computation." In Languages and Compilers for Parallel Computing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-31445-2_2.

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Bibireata, Alina, Sandhya Krishnan, Gerald Baumgartner, et al. "Memory-Constrained Data Locality Optimization for Tensor Contractions." In Languages and Compilers for Parallel Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24644-2_7.

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Vasilache, Nicolas, Oleksandr Zinenko, Aart J. C. Bik, et al. "Structured Operations: Modular Design of Code Generators for Tensor Compilers." In Languages and Compilers for Parallel Computing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-31445-2_10.

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Kaushik, S. D., C. H. Huang, R. W. Johnson, and P. Sadayappan. "A methodology for generating efficient disk-based algorithms from tensor product formulas." In Languages and Compilers for Parallel Computing. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57659-2_21.

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Gupta, S., C. H. Huang, P. Sadayappan, and R. Johnson. "On the synthesis of parallel programs from tensor product formulas for block recursive algorithms." In Languages and Compilers for Parallel Computing. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57502-2_52.

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Liu, Qingzhi, Changbo Chen, and Hanwen Dai. "Accelerating Scientific Computing Kernels by Fusing the Polyhedral and Tensor Compilers." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-90200-0_38.

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Qiu, Chenguang, Jun Wu, Haoqi Ren, and Zhifeng Zhang. "Optimization of Tensor Operation in Compiler." In Communications and Networking. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34790-0_16.

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Rodríguez, Vicente J. Marcet, and Manuel Nevot Navarro. "Historical corpora and linguistic geography of Spanish." In Studies in Corpus Linguistics. John Benjamins Publishing Company, 2023. http://dx.doi.org/10.1075/scl.110.06rod.

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This chapter discusses the evolution of different linguistic phenomena in Castile and León between the 13th and the 16th century. We study four historical corpora consisting of various original notarial and chancellor documents. For this purpose, we have accessed several corpora, representing three main distinct linguistic domains of Castile and León: the North of Burgos, shown in CODOMME; the South of Ávila, collected in CODOMSA and CODAHSA; and the West of León, compiled in CODOMSAE. The examined phenomena were the evolution of compound tenses, the devoicing of sibilants, and the evolution a
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Sulochana, Ms, and U. S. Negi. "CONFORMAL CURVATURE TENSOR COMPILED WITH A METRIC SEMI-SYMMETRIC CONNECTION OF ALMOST HYPERBOLIC TACHIBANA MANIFOLDS." In Futuristic Trends in Contemporary Mathematics & Applications Volume 3 Book 2. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bkcm2p1ch1.

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Negi, et. al. (2019) has established an analytic HP-transformation in almost Kaehlerian spaces. Also, study on Projective recurrent and Symmetric tensor in Almost Kaehlerian Spaces. After that, Negi and Preeti Chauhan (2021), have accomplished Kaehlerian Manifolds with H-Projective and Bochner Recurrent Curvature Tensor of first order. In this chapter, we have calculated Conformal curvature tensor compiled with a metric semi-symmetric connection of Almost Hyperbolic Tachibana Manifolds and some theorems established.
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Fisch, Adam. "White Matter Pathways." In Neuroanatomy : Draw It to Know It. Oxford University PressNew York, NY, 2009. http://dx.doi.org/10.1093/oso/9780195369946.003.0026.

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Abstract White Matter Pathways are the train-tracks of the nervous system. If they are interrupted, impulses stagnate. Historically, the number of publications on white matter has paled in comparison to that on gray matter. However, now, with diffusion tensor imaging and other radiographic techniques dedicated to imaging the white matter pathways, much is being learned about their anatomy. Recent attempts to clarify white matter anatomy using audiographic and diffusion spectrum imaging techniques were compiled in a remarkable book entitled Fiber Pathways of the Brain, by Jeremy Schmahmann and
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Conference papers on the topic "Tensor Compilers"

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Jeon, Gihyeon, and Daejin Park. "Optimizing Multithreaded Access to Global Variables in SPM through Compiler-Enhanced Dependency Analysis." In TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON). IEEE, 2024. https://doi.org/10.1109/tencon61640.2024.10902979.

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Huang, Rui, Zhe Li, Yuxiong Ji, Jing Yang, and Yaohua Wang. "Extensions for compiler infrastructure for neural networks to support automated generation of high-performance tensor programs for DSPs." In Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), edited by Pierluigi Siano and Wenbing Zhao. SPIE, 2024. http://dx.doi.org/10.1117/12.3034293.

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Zumarsyah, Pandega Abyan, Achmad Solaeman, Fhareza Alvindo, and Hanung Adi Nugroho. "Robust Fetal Head Circumference Calculation on Ultrasound Images Using Just-in-Time Compiled Ellipse Fitting." In TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON). IEEE, 2024. https://doi.org/10.1109/tencon61640.2024.10903012.

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Lau, Kingsley, Ivan Lasa, and Mario Paredes. "Update on Corrosion of Post-Tensioned Tendons with Deficient Grout in Florida." In CORROSION 2014. NACE International, 2014. https://doi.org/10.5006/c2014-4225.

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Abstract After recent discovery of corrosion failure of tendons with deficient grout in a Florida bridge, other similar post-tensioned bridges in Florida have been inspected. Other bridges were found to have analogous deficient grout; however, the amount and level of severity of deficient grout varied significantly between bridges. The grout deficiencies appear to be mostly isolated, but instances of significant corrosion of tendon steel components were observed. The deficient grout was found to have high moisture content and enhanced sulfate concentrations. The available data to date was comp
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Jiang, Lijuan, Ping Xu, Qianchao Zhu, et al. "EasyView: Enabling and Scheduling Tensor Views in Deep Learning Compilers." In ICPP '22: 51st International Conference on Parallel Processing. ACM, 2022. http://dx.doi.org/10.1145/3545008.3545037.

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Sioutas, Savvas, Sander Stuijk, Twan Basten, Lou Somers, and Henk Corporaal. "Programming tensor cores from an image processing DSL." In SCOPES '20: 23rd International Workshop on Software and Compilers for Embedded Systems. ACM, 2020. http://dx.doi.org/10.1145/3378678.3391880.

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Groth, Stefan, Jürgen Teich, and Frank Hannig. "Efficient Application of Tensor Core Units for Convolving Images." In SCOPES '21: 24th International Workshop on Software and Compilers for Embedded Systems. ACM, 2021. http://dx.doi.org/10.1145/3493229.3493305.

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Zeng, Xi, Tian Zhi, Zidong Du, Qi Guo, Ninghui Sun, and Yunji Chen. "ALT: Optimizing Tensor Compilation in Deep Learning Compilers with Active Learning." In 2020 IEEE 38th International Conference on Computer Design (ICCD). IEEE, 2020. http://dx.doi.org/10.1109/iccd50377.2020.00108.

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Lin, Zejia, Aoyuan Sun, Xianwei Zhang, and Yutong Lu. "MixPert: Optimizing Mixed-Precision Floating-Point Emulation on GPU Integer Tensor Cores." In LCTES '24: 25th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems. ACM, 2024. http://dx.doi.org/10.1145/3652032.3657567.

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Amaral, José Nelson, Christopher Barton, Andrew C. Macdonell, and Matthew McNaughton. "Using the SGI Pro64 Open Source Compiler Infra-Structure for Teaching and Research." In Simpósio de Arquitetura de Computadores e Processamento de Alto Desempenho. Sociedade Brasileira de Computação, 2001. http://dx.doi.org/10.5753/sbac-pad.2001.22210.

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Modem optimizing compilers are complex programs that require from tens to hundreds of people-years to be developed. Thus professors must use third-party compiler infra-structures to introduce students to compiler optimizations. Until recently only infra-structures developed at universities, research institutes, or by GNU were widely available for teaching. However, in May 2000, SGI made public the source code for Pro64, a highly optimized suite of compilers for the Intel Architecture 64 (IA-64) that is an evolution of the established MIPSPro suite of compilers. The use of a production-level co
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Reports on the topic "Tensor Compilers"

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Nowalski, Jorge, Baltazar Caravedo, Elsa Del Castillo, et al. La responsabilidad social de la empresa en América Latina: Manual de Gestión. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0009873.

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Este libro pretende llenar un vacío en la literatura sobre la Responsabilidad Social de la Empresa en América Latina. Se contactaron destacados académicos, ejecutivos, consultores y expertos en el tema para compilar en un libro los principales conocimientos que los profesionales deben tener en el asunto. En la primera parte, se presenta el QUÉ, los fundamentos conceptuales de la responsabilidad social de la empresa. En la segunda parte, se reflexiona sobre el PORQUÉ de la RSE. Incluye una discusión sobre los principales impulsores de las prácticas de la responsabilidad. La tercera parte del li
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Walker, Michael, Gill Holcombe, Clare Mills, Chiara Nitride, and Adrian Rogers. Development of Reference Materials for food allergen analysis. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.hwt621.

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Food hypersensitivity is an increasing problem for many stakeholders with much effort focused on assessment and management of the risks including risk assessment toolkits (for example, the Allergen Bureau (Opens in a new window) Voluntary Incidental Trace Allergen Labelling VITAL®, the iFAAM consortium (Opens in a new window) and the ILSI-Europe Allergen Quantitative Risk Assessment guidance (Opens in a new window)). These toolkits describe the use of action levels and reference doses to assess the risks. A combination of the estimated eliciting dose of allergenic food, (in milligrams as prote
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