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Performance Evaluation of Checksum-Based ABFT (2001)
| Content Provider | CiteSeerX |
|---|---|
| Author | Al-Yamani, Ahmad A. Oh, Nahmsuk Mccluskey, Edward J. |
| Description | In Algorithm-based fault tolerance (ABFT), fault tolerance is tailored to the algorithm performed. Most of the previous studies that compared ABFT schemes considered only error detection and correction capabilities. Some previous studies looked at the overhead but no previous work --as far as we know-- compared different recovery schemes for data processing applications considering throughput as the main metric. In this work, we compare the performance of two recovery schemes: recomputing and ABFT correction, for different error rates. We consider errors that occur during computation as well as those that occur during error detection, location and correction processes. A metric for performance evaluation of different design alternatives is defined. Results show that multiple error correction using ABFT has poorer performance than single error correction even at high error rates. We also present, implement and evaluate early detection in ABFT. In early detection, we try to detect the errors that occur in the checksum calculation before starting the actual computation. Early detection improves throughput in cases of intensive computations and cases of high error rates. In 16th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (DFT’01 |
| File Format | |
| Language | English |
| Publisher Date | 2001-01-01 |
| Access Restriction | Open |
| Subject Keyword | Single Error Correction Recovery Scheme Checksum Calculation Actual Computation Error Detection Previous Study Correction Process Early Detection Different Design Alternative Different Recovery Scheme Multiple Error Correction Checksum-based Abft High Error Rate Previous Work Intensive Computation Correction Capability Performance Evaluation Abft Correction Data Processing Application Different Error Rate Abft Scheme Fault Tolerance Algorithm-based Fault Tolerance |
| Content Type | Text |
| Resource Type | Article |
