Research Article
Three Strategies for Improving Shortest Vector Enumeration Using GPUs
Algorithm 4
The proposed GPU-based pruned enumeration.
| (1) | Input: basis , and a small integer | | (2) | Compute the quadratic norm of the Gram–Schmidt orthogonalization basis and coefficients and for | | (3) | Generate a better basis using Algorithm 2 | | (4) | Determine the best choice of level using the strategy shown in Section 5.1.2, | | (5) | while true do | | (6) | denotes the number of elements | | (7) | Generate GPU-points on level using Algorithm 3 | | (8) | | | (9) | ifthen | | (10) | Enumerate the GPU-points in on CPU | | (11) | ; | | (12) | end if | | (13) | Copy to GPU memories | | (14) | Start the GPU stage | | (15) | for eachdo | | (16) | if the current enumeration corresponding to a start-point is cut off or reaches level then | | (17) | Produce a neighbor-point of the start-point | | (18) | Calculate for the neighbor-point | | (19) | ifthen | | (20) | The enumeration corresponding to is launched on the current thread | | (21) | else | | (22) | if this start-point is the last point in then | | (23) | Stop enumeration on GPU and return to CPU | | (24) | end if | | (25) | Set a flag that indicates that the start-point terminates its corresponding enumeration | | (26) | Select a new start-point and launch its corresponding enumeration on the current thread | | (27) | end if | | (28) | end if | | (29) | end for each | | (30) | Stop the GPU stage | | (31) | Copy start points that terminate their enumerations in GPU to | | (32) | | | (33) | end while | | (34) | Output: a shorter vector |
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