Title :
Integer Number Crunching on the Cell Processor
Author :
Chen, Hsieh-Chung ; Cheng, Chen-Mou ; Hung, Shih-Hao ; Lin, Zong-Cing
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
We describe our implementation of the Elliptic Curve Method (ECM) of integer factorization on the Cell processor. ECM is the method of choice for finding medium-sized prime factors, e.g., between 230 and 2100. A good ECM implementation is of paramount importance for evaluating the security of cryptosystems like RSA because it is a critical step in the modern versions of the Number Field Sieves (NFS), currently the most efficient cryptanalysis technique against RSA. We use ECM as a benchmark to understand how the performance of integer number crunching applications can benefit from several architectural design features of the Cell including wide arithmetic pipeline, auxiliary pipeline for handling managerial tasks, and large on-die memory per thread of execution. As a result, our ECM implementation on the PowerXCell 8i Cell processor outperforms all previously published implementations on other hardware platforms including graphics processing units (GPUs). For example, compared with the best published result on an NVIDIA GTX 295 graphics card, ours is more than three times faster on absolute basis. This is in spite of the fact that GPUs have greater raw number-crunching capability, not to mention that the Cell consumes less power and hence delivers much better performance per watt.
Keywords :
matrix decomposition; microprocessor chips; public key cryptography; NVIDIA GTX 295 graphics card; PowerXCell 8i Cell processor; Rivest-Shamir-Adleman cryptosystem; cryptanalysis technique; cryptosystems security; elliptic curve method; integer factorization; integer number crunching application; medium-sized prime factors; number field sieves; Computer architecture; Electronic countermeasures; Elliptic curves; Graphics; Instruction sets; Microprocessors; Pipelines; Cell processor; elliptic curve method; integer factorization; multi-core architecture;
Conference_Titel :
Parallel Processing (ICPP), 2010 39th International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7913-9
Electronic_ISBN :
0190-3918
DOI :
10.1109/ICPP.2010.59