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An extended model to support detailed GPGPU reliability analysis, file e384c430-c2cb-d4b2-e053-9f05fe0a1d67
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84
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Programmers manual FlexGripPlus SASS SM 1.0, file e384c433-1977-d4b2-e053-9f05fe0a1d67
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72
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DYRE: a DYnamic REconfigurable solution to increase GPGPU's reliability, file e384c433-46ff-d4b2-e053-9f05fe0a1d67
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47
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Testing permanent faults in pipeline registers of GPGPUs: A multi-kernel approach, file e384c430-f73c-d4b2-e053-9f05fe0a1d67
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46
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On the Functional Test of Special Function Units in GPUs, file e384c433-6926-d4b2-e053-9f05fe0a1d67
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42
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Analyzing the Sensitivity of GPU Pipeline Registers to Single Events Upsets, file e384c432-2c8e-d4b2-e053-9f05fe0a1d67
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36
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On the in-field test of the GPGPU scheduler memory, file e384c430-c927-d4b2-e053-9f05fe0a1d67
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35
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An on-line testing technique for the scheduler memory of a GPGPU, file e384c431-7c3b-d4b2-e053-9f05fe0a1d67
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34
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Evaluating Software-based Hardening Techniques for General-Purpose Registers on a GPGPU, file e384c432-0c9f-d4b2-e053-9f05fe0a1d67
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32
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Using Hardware Performance Counters to support in-field GPU Testing, file e384c433-aa81-d4b2-e053-9f05fe0a1d67
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31
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FlexGripPlus: An improved GPGPU model to support reliability analysis, file e384c431-dbf5-d4b2-e053-9f05fe0a1d67
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25
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High & low-level features modelling of nodes in WSNs using SystemC, file e384c430-d40c-d4b2-e053-9f05fe0a1d67
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23
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On the testing of special memories in GPGPUs, file e384c432-4846-d4b2-e053-9f05fe0a1d67
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22
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A Novel Compaction Approach for SBST Test Programs, file e384c433-d419-d4b2-e053-9f05fe0a1d67
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22
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New Techniques for On-line Testing and Fault Mitigation in GPUs, file e384c434-0311-d4b2-e053-9f05fe0a1d67
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22
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ACELERÓGRAFO TRIAXIAL PORTÁTIL QUE COMPRENDE UN RECEPTOR DE TRAMAS NMEA-GPS, file e384c432-6959-d4b2-e053-9f05fe0a1d67
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20
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Protecting GPU's Microarchitectural Vulnerabilities via Effective Selective Hardening, file e384c433-bac9-d4b2-e053-9f05fe0a1d67
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18
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Untestable faults identification in GPGPUs for safety-critical applications, file e384c431-8403-d4b2-e053-9f05fe0a1d67
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17
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An Effective Method to Identify Microarchitectural Vulnerabilities in GPUs, file e384c434-6f2d-d4b2-e053-9f05fe0a1d67
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16
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Testing the Divergence Stack Memory on GPGPUs: A Modular in-Field Test Strategy, file e384c433-0eb8-d4b2-e053-9f05fe0a1d67
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15
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On the evaluation of SEU effects in GPGPUs, file e384c430-d21f-d4b2-e053-9f05fe0a1d67
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10
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New Techniques for On-line Testing and Fault Mitigation in GPUs, file e384c434-367c-d4b2-e053-9f05fe0a1d67
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8
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About the functional test of the GPGPU scheduler, file e384c430-4386-d4b2-e053-9f05fe0a1d67
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7
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Revealing GPUs Vulnerabilities by Combining Register-Transfer and Software-Level Fault Injection, file e384c434-b6e3-d4b2-e053-9f05fe0a1d67
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7
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Functional Testing with STLs: A Step Towards Reliable RISC-V-based HPC Commodity Clusters, file c0db7b49-2a14-4fc8-b6ea-42efbdf574b1
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5
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Modular Functional Testing: Targeting the Small Embedded Memories in GPUs, file d516c98c-77e0-4ea3-9752-36145f27049f
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5
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Design techniques to improve the resilience of computing systems: software layer, file e384c432-c908-d4b2-e053-9f05fe0a1d67
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5
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An extended model to support detailed GPGPU reliability analysis, file e384c430-dd64-d4b2-e053-9f05fe0a1d67
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4
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Using STLs for Effective In-field Test of GPUs, file b545b482-2588-481c-b26a-9a95edb05935
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3
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On the in-field test of the GPGPU scheduler memory, file e384c430-e080-d4b2-e053-9f05fe0a1d67
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3
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A dynamic hardware redundancy mechanism for the in-field fault detection in cores of GPGPUs, file e384c431-f0e2-d4b2-e053-9f05fe0a1d67
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3
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A dynamic reconfiguration mechanism to increase the reliability of GPGPUs, file e384c431-fe5c-d4b2-e053-9f05fe0a1d67
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3
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FlexGripPlus: An improved GPGPU model to support reliability analysis, file e384c434-70fb-d4b2-e053-9f05fe0a1d67
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3
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Evaluating low-level software-based hardening techniques for configurable GPU architectures, file e384c434-81ed-d4b2-e053-9f05fe0a1d67
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3
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An open source embedded-GPGPU model for the accurate analysis and mitigation of SEU effects, file 4fb2e3cb-4977-4686-a074-a96e5ab72fa0
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2
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Understanding the Effects of Permanent Faults in GPU's Parallelism Management and Control Units, file 99d50e20-4457-446e-953b-8a19dd6f485a
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2
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Untestable faults identification in GPGPUs for safety-critical applications, file e384c431-abc6-d4b2-e053-9f05fe0a1d67
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2
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Design techniques to improve the resilience of computing systems: software layer, file e384c432-c909-d4b2-e053-9f05fe0a1d67
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2
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Improving GPU register file reliability with a comprehensive ISA extension, file e384c432-d16e-d4b2-e053-9f05fe0a1d67
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2
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Design and Verification of an open-source SFU model for GPGPUs, file e384c433-2b3e-d4b2-e053-9f05fe0a1d67
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2
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Revealing GPUs Vulnerabilities by Combining Register-Transfer and Software-Level Fault Injection, file e384c434-877a-d4b2-e053-9f05fe0a1d67
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2
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Evaluating low-level software-based hardening techniques for configurable GPU architectures, file e384c434-af37-d4b2-e053-9f05fe0a1d67
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2
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Using Formal Methods to Support the Development of STLs for GPUs, file ed609920-89f1-464d-a376-68282bc9b70a
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2
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Functional Testing with STLs: A Step Towards Reliable RISC-V-based HPC Commodity Clusters, file 31b99bfe-9b32-41b4-ae1b-fd4ec0fef6b8
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1
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A Multi-level Approach to Evaluate the Impact of GPU Permanent Faults on CNN's Reliability, file 3d7e5f53-31d6-4577-8079-21d6263ade70
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1
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Microarchitectural Reliability Evaluation of a Block Scheduling Controller in GPUs, file 6300e600-7a38-4774-acf0-e3a857cc6699
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1
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A New Method to Generate Software Test Libraries for In-Field GPU Testing Resorting to High-Level Languages, file 6ba2d449-d557-41a1-8410-52b704628b23
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1
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STLs for GPUs: Using High-Level Language Approaches, file 963a188d-be63-409a-aefb-fda32821d05a
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1
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Using Formal Methods to Support the Development of STLs for GPUs, file a91df840-21a3-4f3d-9dc6-edc9ae4c8843
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1
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Understanding the Effects of Permanent Faults in GPU's Parallelism Management and Control Units, file ac2f371f-bdee-4adc-b36f-8ff3e8544ac2
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1
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STLs for GPUs: Using High-Level Language Approaches, file b2d4a5e4-0f24-493f-9ede-f89efc68fbb2
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1
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Evaluating the Impact of Transition Delay Faults in GPUs, file cdf57bfb-74ef-4597-9c0f-7e63a29c05fd
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1
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Evaluating the Impact of Transition Delay Faults in GPUs, file e136334b-1a13-45c0-8d41-a36a5f7cf010
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1
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Evaluating Software-based Hardening Techniques for General-Purpose Registers on a GPGPU, file e384c431-f600-d4b2-e053-9f05fe0a1d67
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1
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On the testing of special memories in GPGPUs, file e384c432-5ad4-d4b2-e053-9f05fe0a1d67
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1
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EQUIPO DESCENTRALIZADO DE PROSPECCIÓN GEOELÉCTRICA DE NODOS RECONFIGURABLES, file e384c432-6acc-d4b2-e053-9f05fe0a1d67
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1
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Testing the Divergence Stack Memory on GPGPUs: A Modular in-Field Test Strategy, file e384c433-29aa-d4b2-e053-9f05fe0a1d67
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1
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On the Functional Test of Special Function Units in GPUs, file e384c433-8832-d4b2-e053-9f05fe0a1d67
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1
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Protecting GPU's Microarchitectural Vulnerabilities via Effective Selective Hardening, file e384c433-a951-d4b2-e053-9f05fe0a1d67
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1
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Combining architectural simulation and software fault injection for a fast and accurate CNNs reliability evaluation on GPUs, file e384c433-efb4-d4b2-e053-9f05fe0a1d67
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1
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A Reliability-aware Environment for Design Exploration for GPU Devices, file eccd40aa-f68b-4963-9850-5faedc551a66
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1
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| Totale |
764 |
Archivio Istituzionale della Ricerca