Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00007
B. Joó, T. Kurth, M. A. Clark, Jeongnim Kim, C. Trott, Daniel Ibanez, Daniel Sunderland, J. Deslippe
We describe our experiences in creating mini-apps for the Wilson-Dslash stencil operator for Lattice Quantum Chromodynamics using the Kokkos and SYCL programming models. In particular we comment on the performance achieved on a variety of hardware architectures, limitations we have reached in both programming models and how these have been resolved by us, or may be resolved by the developers of these models.
{"title":"Performance Portability of a Wilson Dslash Stencil Operator Mini-App Using Kokkos and SYCL","authors":"B. Joó, T. Kurth, M. A. Clark, Jeongnim Kim, C. Trott, Daniel Ibanez, Daniel Sunderland, J. Deslippe","doi":"10.1109/P3HPC49587.2019.00007","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00007","url":null,"abstract":"We describe our experiences in creating mini-apps for the Wilson-Dslash stencil operator for Lattice Quantum Chromodynamics using the Kokkos and SYCL programming models. In particular we comment on the performance achieved on a variety of hardware architectures, limitations we have reached in both programming models and how these have been resolved by us, or may be resolved by the developers of these models.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134478909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/p3hpc49587.2019.00002
{"title":"[Copyright notice]","authors":"","doi":"10.1109/p3hpc49587.2019.00002","DOIUrl":"https://doi.org/10.1109/p3hpc49587.2019.00002","url":null,"abstract":"","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116650548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00010
D. Daniel, J. Panetta
As we prepare for further technological advance- ment in supercomputing, the diversity of hardware architec- tures and parallel programming languages has increased to new levels. At the same time, extracting performance from so many architectures is even more difficult. In this context, the appearance of portable languages capable of generating executable code for multiple architectures has become a recurrent research target. We port a set of seven parallel benchmarks from SPEC ACCEL suite and a wave propagation code to one such portable language: the Kokkos C++ programming library. Using the original OpenACC versions of the eight codes, we apply a known performance portability metric on the OpenACC and Kokkos versions of those codes across a variety of hardware platforms and problem sizes. We observe that the portability metric is sensitive to the problem size. To remedy this deficiency, we propose a novel metric for performance portability, apply the proposed metric to the eight codes and discuss the results.
{"title":"On Applying Performance Portability Metrics","authors":"D. Daniel, J. Panetta","doi":"10.1109/P3HPC49587.2019.00010","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00010","url":null,"abstract":"As we prepare for further technological advance- ment in supercomputing, the diversity of hardware architec- tures and parallel programming languages has increased to new levels. At the same time, extracting performance from so many architectures is even more difficult. In this context, the appearance of portable languages capable of generating executable code for multiple architectures has become a recurrent research target. We port a set of seven parallel benchmarks from SPEC ACCEL suite and a wave propagation code to one such portable language: the Kokkos C++ programming library. Using the original OpenACC versions of the eight codes, we apply a known performance portability metric on the OpenACC and Kokkos versions of those codes across a variety of hardware platforms and problem sizes. We observe that the portability metric is sensitive to the problem size. To remedy this deficiency, we propose a novel metric for performance portability, apply the proposed metric to the eight codes and discuss the results.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114624544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00012
D. Beckingsale, T. Scogland, J. Burmark, R. Hornung, Holger E. Jones, W. Killian, A. Kunen, Olga Pearce, P. Robinson, B. Ryujin
Modern high-performance computing systems are diverse, with hardware designs ranging from homogeneous multi- core CPUs to GPU or FPGA accelerated systems. Achieving desir- able application performance often requires choosing a program- ming model best suited to a particular platform. For large codes used daily in production that are under continual development, architecture-specific ports are untenable. Maintainability re- quires single-source application code that is performance portable across a range of architectures and programming models. In this paper we describe RAJA, a portability layer that enables C++ applications to leverage various programming models, and thus architectures, with a single-source codebase. We describe preliminary results using RAJA in three large production codes at Lawrence Livermore National Laboratory, observing 17×, 13× and 12× speedup on GPU-only over CPU- only nodes with single-source application code in each case.
{"title":"RAJA: Portable Performance for Large-Scale Scientific Applications","authors":"D. Beckingsale, T. Scogland, J. Burmark, R. Hornung, Holger E. Jones, W. Killian, A. Kunen, Olga Pearce, P. Robinson, B. Ryujin","doi":"10.1109/P3HPC49587.2019.00012","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00012","url":null,"abstract":"Modern high-performance computing systems are diverse, with hardware designs ranging from homogeneous multi- core CPUs to GPU or FPGA accelerated systems. Achieving desir- able application performance often requires choosing a program- ming model best suited to a particular platform. For large codes used daily in production that are under continual development, architecture-specific ports are untenable. Maintainability re- quires single-source application code that is performance portable across a range of architectures and programming models. In this paper we describe RAJA, a portability layer that enables C++ applications to leverage various programming models, and thus architectures, with a single-source codebase. We describe preliminary results using RAJA in three large production codes at Lawrence Livermore National Laboratory, observing 17×, 13× and 12× speedup on GPU-only over CPU- only nodes with single-source application code in each case.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124117044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00009
John K. Holmen, B. Peterson, M. Berzins
Diversity among supported architectures in current and emerging high performance computing systems, including those for exascale, makes portable codebases desirable. Portabil- ity of a codebase can be improved using a performance portability layer to provide access to multiple underlying programming mod- els through a single interface. Direct adoption of a performance portability layer, however, poses challenges for large pre-existing software frameworks that may need to preserve legacy code and/or adopt other programming models in the future. This paper describes an approach for indirect adoption that introduces a framework-specific portability layer between the application developer and the adopted performance portability layer to help improve legacy code support and long-term portability for future architectures and programming models. This intermediate layer uses loop-level, application-level, and build-level components to ease adoption of a performance portability layer in large legacy codebases. Results are shown for two challenging case studies using this approach to make portable use of OpenMP and CUDA via Kokkos in an asynchronous many-task runtime system, Uintah. These results show performance improvements up to 2.7x when refactoring for portability and 2.6x when more efficiently using a node. Good strong-scaling to 442,368 threads across 1,728 Knights Landing processors are also shown using MPI+Kokkos at scale.
{"title":"An Approach for Indirectly Adopting a Performance Portability Layer in Large Legacy Codes","authors":"John K. Holmen, B. Peterson, M. Berzins","doi":"10.1109/P3HPC49587.2019.00009","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00009","url":null,"abstract":"Diversity among supported architectures in current and emerging high performance computing systems, including those for exascale, makes portable codebases desirable. Portabil- ity of a codebase can be improved using a performance portability layer to provide access to multiple underlying programming mod- els through a single interface. Direct adoption of a performance portability layer, however, poses challenges for large pre-existing software frameworks that may need to preserve legacy code and/or adopt other programming models in the future. This paper describes an approach for indirect adoption that introduces a framework-specific portability layer between the application developer and the adopted performance portability layer to help improve legacy code support and long-term portability for future architectures and programming models. This intermediate layer uses loop-level, application-level, and build-level components to ease adoption of a performance portability layer in large legacy codebases. Results are shown for two challenging case studies using this approach to make portable use of OpenMP and CUDA via Kokkos in an asynchronous many-task runtime system, Uintah. These results show performance improvements up to 2.7x when refactoring for portability and 2.6x when more efficiently using a node. Good strong-scaling to 442,368 threads across 1,728 Knights Landing processors are also shown using MPI+Kokkos at scale.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125553885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00008
I. Reguly
Trying to improve performance, portability, and productivity of an application presents non-trivial trade-offs, which are often difficult to quantify. Recent work has developed metrics for performance portability, as well some aspects of productivity - in this case study, we present a set of challeng- ing computational kernels and their implementations from the domain of multi-material simulations, and evaluate them using these metrics. Three key kernels are implemented using OpenMP, OpenMP offload, OpenACC, CUDA, SYCL, and KOKKOS, and tested on ARM ThunderX2, IBM Power 9, Intel KNL, Broadwell, and Skylake CPUs, as well as NVIDIA P100 and V100 GPUs. We also consider the choice of compilers, evaluating LLVM/Clang, GCC, PGI, Intel, IBM XL, and Cray compilers, where available. We present a detailed performance analysis, calculate performance portability and code divergence metrics, contrasting performance, portability, and productivity.
试图提高应用程序的性能、可移植性和生产力会带来一些重要的权衡，而这些权衡通常很难量化。最近的工作已经开发了性能可移植性的指标，以及生产力的某些方面-在本案例研究中，我们提出了一组具有挑战性的计算内核及其来自多材料模拟领域的实现，并使用这些指标对它们进行评估。使用OpenMP, OpenMP卸载，OpenACC, CUDA, SYCL和KOKKOS实现了三个关键内核，并在ARM ThunderX2, IBM Power 9, Intel KNL, Broadwell和Skylake cpu以及NVIDIA P100和V100 gpu上进行了测试。我们还考虑了编译器的选择，评估了LLVM/Clang、GCC、PGI、Intel、IBM XL和Cray编译器(如果可用)。我们提供了详细的性能分析，计算性能可移植性和代码发散度量，对比性能、可移植性和生产力。
{"title":"Performance Portability of Multi-Material Kernels","authors":"I. Reguly","doi":"10.1109/P3HPC49587.2019.00008","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00008","url":null,"abstract":"Trying to improve performance, portability, and productivity of an application presents non-trivial trade-offs, which are often difficult to quantify. Recent work has developed metrics for performance portability, as well some aspects of productivity - in this case study, we present a set of challeng- ing computational kernels and their implementations from the domain of multi-material simulations, and evaluate them using these metrics. Three key kernels are implemented using OpenMP, OpenMP offload, OpenACC, CUDA, SYCL, and KOKKOS, and tested on ARM ThunderX2, IBM Power 9, Intel KNL, Broadwell, and Skylake CPUs, as well as NVIDIA P100 and V100 GPUs. We also consider the choice of compilers, evaluating LLVM/Clang, GCC, PGI, Intel, IBM XL, and Cray compilers, where available. We present a detailed performance analysis, calculate performance portability and code divergence metrics, contrasting performance, portability, and productivity.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116737442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/P3HPC49587.2019.00011
D. Hollman, B. Lelbach, H. Edwards, M. Hoemmen, Daniel Sunderland, C. Trott
Multi-dimensional arrays are ubiquitous in high-performance computing (HPC), but their absence from the C++ language standard is a long-standing and well-known limitation of their use for HPC. This paper describes the design and implementation of mdspan, a proposed C++ standard multidimensional array view (planned for inclusion in C++23). The proposal is largely inspired by work done in the Kokkos project— a C++ performance-portable programming model de- ployed by numerous HPC institutions to prepare their code base for exascale-class supercomputing systems. This paper describes the final design of mdspan af- ter a five-year process to achieve consensus in the C++ community. In particular, we will lay out how the design addresses some of the core challenges of performance-portable programming, and how its cus- tomization points allow a seamless extension into areas not currently addressed by the C++ Standard but which are of critical importance in the heterogeneous computing world of today’s systems. Finally, we have provided a production-quality implementation of the proposal in its current form. This work includes several benchmarks of this implementation aimed at demon- strating the zero-overhead nature of the modern design.
{"title":"mdspan in C++: A Case Study in the Integration of Performance Portable Features into International Language Standards","authors":"D. Hollman, B. Lelbach, H. Edwards, M. Hoemmen, Daniel Sunderland, C. Trott","doi":"10.1109/P3HPC49587.2019.00011","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00011","url":null,"abstract":"Multi-dimensional arrays are ubiquitous in high-performance computing (HPC), but their absence from the C++ language standard is a long-standing and well-known limitation of their use for HPC. This paper describes the design and implementation of mdspan, a proposed C++ standard multidimensional array view (planned for inclusion in C++23). The proposal is largely inspired by work done in the Kokkos project— a C++ performance-portable programming model de- ployed by numerous HPC institutions to prepare their code base for exascale-class supercomputing systems. This paper describes the final design of mdspan af- ter a five-year process to achieve consensus in the C++ community. In particular, we will lay out how the design addresses some of the core challenges of performance-portable programming, and how its cus- tomization points allow a seamless extension into areas not currently addressed by the C++ Standard but which are of critical importance in the heterogeneous computing world of today’s systems. Finally, we have provided a production-quality implementation of the proposal in its current form. This work includes several benchmarks of this implementation aimed at demon- strating the zero-overhead nature of the modern design.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"666 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123050866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-25DOI: 10.1109/P3HPC49587.2019.00006
Tom Deakin, Simon McIntosh-Smith, J. Price, Andrei Poenaru, Patrick Atkinson, Codrin Popa, Justin Salmon
Previous studies into performance portability have typically analysed a single application (and its various imple- mentations) in isolation. In this study we explore the wider landscape of performance portability by considering a number of applications from across the space of dwarfs, written in multiple parallel programming models, and across a diverse set of architectures. We apply rigorous performance portability metrics, as defined by Pennycook et al [1]. We believe this is the broadest and most rigorous performance portability study to date, representing a far reaching exploration of the state of performance portability that is achievable today. We will present a summary of the performance portability of each application and programming model across our diverge range of twelve computer architectures, including six different server CPUs from five different vendors, five different GPUs from two different vendors, and one vector architecture. We will conclude with an analysis of the performance portability of key programming models in general, across different application spaces as well across differing architectures, allowing us to comment on more general performance portability principles.
{"title":"Performance Portability across Diverse Computer Architectures","authors":"Tom Deakin, Simon McIntosh-Smith, J. Price, Andrei Poenaru, Patrick Atkinson, Codrin Popa, Justin Salmon","doi":"10.1109/P3HPC49587.2019.00006","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00006","url":null,"abstract":"Previous studies into performance portability have typically analysed a single application (and its various imple- mentations) in isolation. In this study we explore the wider landscape of performance portability by considering a number of applications from across the space of dwarfs, written in multiple parallel programming models, and across a diverse set of architectures. We apply rigorous performance portability metrics, as defined by Pennycook et al [1]. We believe this is the broadest and most rigorous performance portability study to date, representing a far reaching exploration of the state of performance portability that is achievable today. We will present a summary of the performance portability of each application and programming model across our diverge range of twelve computer architectures, including six different server CPUs from five different vendors, five different GPUs from two different vendors, and one vector architecture. We will conclude with an analysis of the performance portability of key programming models in general, across different application spaces as well across differing architectures, allowing us to comment on more general performance portability principles.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127084489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-18DOI: 10.1109/P3HPC49587.2019.00013
H. Finkel, David Poliakoff, D. Richards
The C++ programming language is not only a keystone of the high-performance-computing ecosystem but has proven to be a successful base for portable parallel-programming frameworks. As is well known, C++ programmers use templates to specialize algorithms, thus allowing the compiler to generate highly-efficient code for specific parameters, data structures, and so on. This capability has been limited to those specializations that can be identified when the application is compiled, and in many critical cases, compiling all potentially-relevant specializations is not practical. ClangJIT provides a well-integrated C++ language extension allowing template-based specialization to occur during program execution. This capability has been implemented for use in large-scale applications, and we demonstrate that just-in-time- compilation-based dynamic specialization can be integrated into applications, often requiring minimal changes (or no changes) to the applications themselves, providing significant performance improvements, programmer-productivity improvements, and de- creased compilation time.
{"title":"ClangJIT: Enhancing C++ with Just-in-Time Compilation","authors":"H. Finkel, David Poliakoff, D. Richards","doi":"10.1109/P3HPC49587.2019.00013","DOIUrl":"https://doi.org/10.1109/P3HPC49587.2019.00013","url":null,"abstract":"The C++ programming language is not only a keystone of the high-performance-computing ecosystem but has proven to be a successful base for portable parallel-programming frameworks. As is well known, C++ programmers use templates to specialize algorithms, thus allowing the compiler to generate highly-efficient code for specific parameters, data structures, and so on. This capability has been limited to those specializations that can be identified when the application is compiled, and in many critical cases, compiling all potentially-relevant specializations is not practical. ClangJIT provides a well-integrated C++ language extension allowing template-based specialization to occur during program execution. This capability has been implemented for use in large-scale applications, and we demonstrate that just-in-time- compilation-based dynamic specialization can be integrated into applications, often requiring minimal changes (or no changes) to the applications themselves, providing significant performance improvements, programmer-productivity improvements, and de- creased compilation time.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122212825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-01-01DOI: 10.5040/9781350046436.ch-005
Simon Bell
The post- Cartesian ‘material turn’ in management and organization studies understands that bodies are far more than vehicles that enable work to be undertaken, but are agentive actors in the constitution of work and working selves. This leads to the need for more empirically-derived understanding of the agency of flesh in the performative corporealization of working, embodied selves. We met this challenge through adapting feminist, posthuman research methods for a study of the materialities and materialization of working bodies . The study takes forward Judith Butler’s and Karen Barad’s theories of performativity by reading them through each other, and introducing flesh as an agentive actor in each moment-to-moment move. In paying close attention to the speech of supposedly ‘dumb flesh’ we show how flesh resists its negation and itself imposes control on the worker. We coin the term ‘body/flesh’ and illuminate how bodies are active and agentive, constituting corporeal/izing working selves in somewhat unexpected ways.
{"title":"Organization","authors":"Simon Bell","doi":"10.5040/9781350046436.ch-005","DOIUrl":"https://doi.org/10.5040/9781350046436.ch-005","url":null,"abstract":"The post- Cartesian ‘material turn’ in management and organization studies understands that bodies are far more than vehicles that enable work to be undertaken, but are agentive actors in the constitution of work and working selves. This leads to the need for more empirically-derived understanding of the agency of flesh in the performative corporealization of working, embodied selves. We met this challenge through adapting feminist, posthuman research methods for a study of the materialities and materialization of working bodies . The study takes forward Judith Butler’s and Karen Barad’s theories of performativity by reading them through each other, and introducing flesh as an agentive actor in each moment-to-moment move. In paying close attention to the speech of supposedly ‘dumb flesh’ we show how flesh resists its negation and itself imposes control on the worker. We coin the term ‘body/flesh’ and illuminate how bodies are active and agentive, constituting corporeal/izing working selves in somewhat unexpected ways.","PeriodicalId":377385,"journal":{"name":"2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127985662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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