搜索结果: 1-15 共查到“GPUs”相关记录15条 . 查询时间(0.037 秒)
Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs（图）
GPU 流水线 大型图形 深度学习
2023/6/20
Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy gri...
The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs
Fully Homomorphic Encryption Deep Learning Encrypted CNN
2018/11/2
Fully homomorphic encryption, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned cloud applications including deep learning as a service. This com...
Implementing Joux-Vitse's Crossbred Algorithm for Solving MQ Systems over GF(2) on GPUs
Post-quantum cryptography multivariate quadratic systems parallel implementation
2017/12/11
The hardness of solving multivariate quadratic (MQ) systems is the underlying problem for multivariate-based schemes in the field of post-quantum cryptography. The concrete, practical hardness of this...
Singe: Leveraging Warp Specialization for High Performance on GPUs
warp specialization warp-specializing compiler GPU DSL
2016/5/24
We present Singe, a Domain Specific Language (DSL) compiler for combustion chemistry that leverages warp specialization to produce high performance code for GPUs. Instead of relying on traditional GPU...
NTRU Modular Lattice Signature Scheme on CUDA GPUs
NTRU digital signatures lattice techniques
2016/5/18
In this work we show how to use Graphics Processing Units (GPUs) with Compute Unified Device Architecture (CUDA) to accelerate a lattice based signature scheme, namely, the NTRU modular lattice signat...
In this work we introduce a large polynomial arithmetic library optimized for Nvidia GPUs to support fully homomorphic encryption schemes. To realize the large polynomial arithmetic library we convert...
Accelerating SWHE based PIRs using GPUs
Private information retrieval homomorphic encryption NTRU
2015/12/30
In this work we focus on tailoring and optimizing the computational
Private Information Retrieval (cPIR) scheme proposed in
WAHC 2014 for efficient execution on graphics processing units (GPUs).
Ex...
Investigating SRAM PUFs in large CPUs and GPUs
Physically unclonable functions SRAM PUFs randomness
2015/12/24
Physically unclonable functions (PUFs) provide data
that can be used for cryptographic purposes: on the one hand randomness
for the initialization of random-number generators; on the
other hand ind...
Porting marine ecosystem model spin-up using transport matrices to GPUs
Porting marine ecosystem model spin-up transport matrices GPUs
2014/12/17
We have ported an implementation of the spin-up for marine ecosystem models based on transport matrices to graphics processing units (GPUs). The original implementation was designed for distributed-me...
ASAMgpu V1.0 – a moist fully compressible atmospheric model using graphics processing units (GPUs)
ASAM gpu V1.0 compressible atmospheric model graphics processing units
2014/12/11
In this work the three dimensional compressible moist atmospheric model ASAMgpu is presented. The calculations are done using graphics processing units (GPUs). To ensure platform independence OpenGL a...
Implementation Of Decoders for LDPC Block Codes and LDPC Convolutional Codes Based on GPUs
Implementation Of Decoders LDPC Block Codes LDPC Convolutional Codes GPUs
2012/4/17
With the use of belief propagation (BP) decoding algorithm, low-density parity-check (LDPC) codes can achieve near-Shannon limit performance. LDPC codes can accomplish bit error rates (BERs) as low as...
Accelerating Lossless Data Compression with GPUs
Accelerating Lossless Data GPUs Information Theory Graphics
2011/8/30
Abstract: Huffman compression is a statistical, lossless, data compression algorithm that compresses data by assigning variable length codes to symbols, with the more frequently appearing symbols give...
Massively parallelized replica-exchange simulations of polymers on GPUs
GPU CUDA Monte Carlo simulations parallel tempering polymers structural transitions
2011/8/5
Abstract: We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) for parallel tempering Monte Carlo computer simulations of an exemplified bead-spring model...
We report on our implementation of the RHMC algorithm for the simulation of lattice QCD with two staggered flavors on Graphics Processing Units, using the NVIDIA CUDA programming language. The main fe...
We describe an algorithm for computing an inverse spherical harmonic transform suitable for graphic processing units (GPU). We use CUDA and base our implementation on a Fortran90 routine included in ...