![]() ![]() We highlight challenges and opportunities that the future holds in the area of system software technology for neuromorphic computing. In the present age of high density integrated circuits, radiation induced adjacent muti-bit upsets (AMBUs) or clustered errors are very prominent in the configuration memory of static random access memory (SRAM) based Field Programmable Gate Array (FPGA) devices. Radiated particles with high energy and low momentum may damage a group of adjacent logic cells and switches in reconfigurable devices, which can lead to clustered errors. Commonly used error mitigation techniques in FPGA either have large overheads, complex decoding circuitry or are not very efficient to correct AMBUs. Hence, efficient multi-bit error correcting codes with low redundancy is of utmost need to mitigate the effect of AMBUs. Configuration data of the FPGAs are composed of a number of configuration frames (CFs) and there is a high probability that multiple physically adjacent CFs may be affected by clustered error. In this paper we have proposed a simple and efficient error mitigation model combining Hence, interleaving among CFs are quite advantageous for mitigation of clustered errors in the configuration memory of FPGA. , termed as ‘HPCFISBP’ to correct AMBUs in the configuration memory of FPGA without any modification in its basic architecture. HPCFISBP provides better bit error rate (BER) performance nearly by 20 dB and 10 dB compared to Hamming code and HPC respectively. The enhanced performance of HPCFISBP has also been established through comparison with the state of the art techniques in terms of error correction coverage, error correction time, redundancy and residual error. Reliability is an important design constraint for critical applications at ground-level and aero-space. ![]() SRAM-based FPGAs are attractive for critical applications due to their high perfor-mance and flexibility. However, they are susceptible to radiation effects such as soft errors inthe configuration memory. Furthermore, the effects of aging and voltage scaling increment thesensitivity of SRAM-based FPGAs to soft errors. Experimental results show that aging and voltage scaling can increase at least two times the susceptibility of SRAM-based FPGAs toSoft Error Rate (SER). *Note: Read the following Microsoft page if these steps do not work on Windows 7.These findings are innovative because they combine three real effectsthat occur in SRAM-based FPGAs. ![]() In the Search Computer/This PC input box, type:.For Windows 8, 8.1, and Server 2012 users, right-click on the lower left corner of the screen, then click File Explorer.For Windows Vista, 7, and Server 2008 users, click Start>Computer.For Windows Vista, Windows 7, Windows Server 2008, Windows 8, Windows 8.1, and Windows Server 2012:.Search for files or folders named or All or part of the file name.). *Note: The file name input box title varies depending on the Windows version (e.g. Once located, select the file then press SHIFT+DELETE to delete it.In the Look In drop-down list, select My Computer then press Enter.In the File name* input box, type the following:.For Windows 2000, Windows XP, and Windows Server 2003:.To manually delete a malware/grayware file from an affected system: This Trojan arrives on a system as a file dropped by other malware or as a file downloaded unknowingly by users when visiting malicious sites.
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