209 research outputs found

    Super Calculator using Compute Unified Device Architecture (CUDA)

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    Scientific computation requires a great amount of computing power especially in floating-point operation but a high-end multi-cores processor is currently limited in terms of floating point operation performance and parallelization. Recent technological advancement has made parallel computing technically and financially feasible using Compute Unified Device Architecture (CUDA) developed by NVIDIA. This research focuses on measuring the performance of CUDA and implementing CUDA for a scientific computation involving the process of porting the source code from CPU to GPU using direct integration technique. The ported source code is then optimized by managing the resources to achieve performance gain over CPU. It is found that CUDA is able to boost the performance of the system up to 69 times in Parboil Benchmark Suite. Successful attempt at porting Serpent encryption algorithm and Lattice Boltzmann Method provided up to 7 times throughput performance gain and up to 10 times execution time performance gain respectively over the CPU. Direct integration guideline for porting the source code is then produced based on the two implementations

    CUDA capable GPU as an efficient co-processor

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    PRISEC: Comparison of Symmetric Key Algorithms for IoT Devices

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    With the growing number of heterogeneous resource-constrained devices connected to the Internet, it becomes increasingly challenging to secure the privacy and protection of data. Strong but efficient cryptography solutions must be employed to deal with this problem, along with methods to standardize secure communications between these devices. The PRISEC module of the UbiPri middleware has this goal. In this work, we present the performance of the AES (Advanced Encryption Standard), RC6 (Rivest Cipher 6), Twofish, SPECK128, LEA, and ChaCha20-Poly1305 algorithms in Internet of Things (IoT) devices, measuring their execution times, throughput, and power consumption, with the main goal of determining which symmetric key ciphers are best to be applied in PRISEC. We verify that ChaCha20-Poly1305 is a very good option for resource constrained devices, along with the lightweight block ciphers SPECK128 and LEA.info:eu-repo/semantics/publishedVersio

    Analysis of Advanced Encryption Standards

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    The Advanced Encryption Standard (AES),the block cipher ratified as a standard by National Instituteof Standards and Technology of the United States (NIST), waschosen using a process markedly more open and transparentthan its predecessor, the aging Data Encryption Standard(DES).Fifteen algorithm were submitted as to NIST in 1998 ,NIST choose five finalist.NIST primary selection criteria are security, performance,and flexibility. This paper enlightens the last two criteria. Inthis paper we have discussed software performance of five AESfinalist.The paper specifically compares performance of the fiveAES finalist on a verity of common software platform: 32-bitCPU( both large and smaller microprocessors, smart cards,embedded microprocessors) and high end 64-bits CPUs

    Super Calculator using Compute Unified Device Architecture (CUDA)

    Get PDF
    Scientific computation requires a great amount of computing power especially in floating-point operation but a high-end multi-cores processor is currently limited in terms of floating point operation performance and parallelization. Recent technological advancement has made parallel computing technically and financially feasible using Compute Unified Device Architecture (CUDA) developed by NVIDIA. This research focuses on measuring the performance of CUDA and implementing CUDA for a scientific computation involving the process of porting the source code from CPU to GPU using direct integration technique. The ported source code is then optimized by managing the resources to achieve performance gain over CPU. It is found that CUDA is able to boost the performance of the system up to 69 times in Parboil Benchmark Suite. Successful attempt at porting Serpent encryption algorithm and Lattice Boltzmann Method provided up to 7 times throughput performance gain and up to 10 times execution time performance gain respectively over the CPU. Direct integration guideline for porting the source code is then produced based on the two implementations
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