1 OpenSSL acceleration using Graphics Processing Units Pedro Miguel Costa Saraiva

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OpenSSL acceleration using Graphics

Processing Units

Pedro Miguel Costa Saraiva

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Introduction•Cryptography: The study of

security techniques

•SSL: A set of rules governing authentication and encrypted client/server communication• De facto standard for secure electronic

communications

• Computationally intensive

• Large volumes of SSL traffic impact performance


OpenSSL acceleration using Graphics Processing Units

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Introduction

•GPU: A specialised processing unit designed to manipulate graphics• Originally used solely for graphics calculations

• Recent developments enable its use for general purpose computing

• Massive computational power



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Introduction

•OpenSSL• Open-source implementation of the SSL and

TLS protocols

• Core-library implements a variety of cryptographic functions

• Intensively used by an extremely large number of both open and proprietary applications



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Introduction

•Objectives• Efficiently offload cryptographic operations

onto a GPU

• Add GPU functionality to OpenSSL

• Lighten the load on the CPU



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Introduction•Structure

• State of the art• OpenSSL

• GPU

• Programming the GPU

• OpenCL

• CUDA

• OpenCL vs CUDA

• Main challenges

• Implementation

• Results

• Conclusion



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State of the art

•OpenSSL

• Commercial-grade full-featured open source toolkit

• Divided into libssl and libcrypto

• Core library written in C

• Supports accelerator hardware via engines



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State of the art

• Massive parallel processing power

• Roughly ten times the floating point capability of a high end CPU

• Faster growth rate than CPUs


GPU


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State of the art

• At the end of the 90s, graphics cards could not be programmed

• Things changed in 2001 with the release of DirectX 8 and OpenGL

• Programmers had to express their computations in terms of textures, vertices and shader programs


GPU - Programming


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State of the art

• 2006: NVIDIA created the CUDA framework

• ATI created the CTM low-level framework

• 2008: NVIDIA and ATI joined the Khronos Group

• Development of an industry standard for hybrid computing

• OpenCL version 1.0 released in December 2008


GPU - Programming


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State of the art

• Open, royalty-free standard for general purpose programming

• Supports CPUs, GPUs, and other types of processors

• Maintained by the non-profit consortium Khronos Group

• Adopted by Intel, AMD, NVIDIA, and ARM Holdings


GPU - OpenCL


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State of the art

• API for coordinating parallel computation across different processors

• Cross-platform programming languages

• Subset of ISO C99

• Low performance on NVIDIA GPUs


GPU - OpenCL


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State of the art

• Proprietary hardware and software architecture

• Designed by NVIDIA

• Manages computations on a GPU

• API is programmed with “C for CUDA”

• Third party wrappers available for other languages


GPU - CUDA


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State of the art

• Well suited to extremely parallel problems

• Interaction between threads should be minimal

• Diverging executions paths are slow

• Limited memory

• Slow memory swapping

• Data-intensive operations are discouraged

• No file or standard I/O operations


GPU - Main Challenges


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Implementation

• OpenSSL

• AES

• RSA Key Generation

• RSA Cipher


Structure


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Implementation

• ENGINE component supports alternative cryptography implementations

• Supports dynamic loading of external engines


OpenSSL


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Implementation

• Binding function defines supported algorithms

• Pointers to functions implementing the defined algorithms


OpenSSL Engine


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Implementation

• CBC mode encryption cannot be parallelised

• Previous ciphertext block is required to begin encryption of the next one

• CBC mode decryption can be parallelised

• All blocks are decrypted in parallel

• ECB mode can be parallelised


AES


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Implementation

• Initialisation

• Key expansion is performed on the CPU

• Cipher

• Initialises the GPU

• Allocates host and GPU memory for input and output data


AES


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Implementation

• Cipher

• Input data transferred to the GPU memory

• All data transferred at once

• GPU Kernel is called

• Output data is transferred from the GPU memory


AES


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Implementation

• GPU Kernel

• For CBC encryption, a single thread is called

• Encrypts every block serially

• For CBC decryption and ECB operations, a thread is called for every block

• All blocks are processed in parallel


AES


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Implementation

• Generation function (CPU side)

• Calls the GPU to generate a large amount of prime candidates

• No more numbers are generated until the initial pool is exhausted


RSA Key Generation


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Implementation

• Generation function (GPU call)

• GPU RNG is initialised

• Device memory is allocated

• A large amount of threads is called to generate prime BIGNUMs


RSA Key Generation


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Implementation

• Generation function (GPU kernel)

• Random BIGNUM is generated

• BIGNUM p is tested for primality

• Miller-Rabin probabilistic primality test

• BIGNUMs determined to be prime are written into global memory

• Each thread tests one BIGNUM


RSA Key Generation


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Implementation

• Generation function (GPU call)

• Output data copied back to the host

• Required implementing the entire OpenSSL BIGNUM library on the GPU


RSA Key Generation


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Implementation

• BIGNUMs used in RSA must be broken down into small words

• Multiple threads can each process a word

• Chinese Remainder Theorem can split private key operations in half


RSA Cipher


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Implementation

• Multi-Precision Algorithm

• K-bit integer A is broken into s k/64 words

• O(s) parallel implementation

• Runs s threads in two phases


RSA Cipher


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Implementation

• First phase accumulates s partial products in 2s steps

• Carries accumulated in a separate array

• Second phase adds the carries to the intermediate result\

• Worst case scenario is s-1 iterations

• Usually only one or two


RSA Cipher


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Results

• Intel Core i7 950 CP, 3.07GHz

• NVIDIA GeForce GTX 580

• Stress tool used on heavy CPU load tests

• 300 threads looping on sqrt, malloc/free and sync


Testing Framework


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Results


AES – CBC Decryption


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Results


AES – CBC Encryption


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Results


AES – ECB Encryption


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Results


AES – ECB Decryption


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Results


RSA Key Generation


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Results


RSA Key Generation – Heavy CPU load


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Results


RSA Cipher


Single message, heavy CPU load

RSA Cipher

Single message

Multiple messages (4096-bit)

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Results




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Results




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Conclusion



• Significant performance boost for AES ECB and CBC Decryption

• AES CBC Encryption is slower, but significantly lighter on the CPU

• RSA Key Generation is significantly faster for multiple keys

• RSA Cipher is significantly slower

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Future Work



• AES CTR Cipher Mode

• OpenSSL implementation still unstable

• Manager to cache RSA requests for more effective use of the GPU

Documents

1 OpenSSL acceleration using Graphics Processing Units Pedro Miguel Costa Saraiva