Table 11 Summary of SW implementations on accelerators and low-power devices over the past five years
From: DNA sequences alignment in multi-GPUs: acceleration and energy payoff
Device | Hardware model | Power | Implementation | Input size | GCUPS | GCUPS/W | Ref. |
|---|---|---|---|---|---|---|---|
FPGA | Altera Stratix V | 25 W (a) | OpenCL | 23Mx25M | 37.67 | 1.50 | [34] |
Accel. | Intel Xeon Phi 3120P | 270 W (a) | OpenCL | 23Mx25M | 30.36 | 0.12 | [34] |
GPU | Nvidia Tesla K20 | 225 W (a) | SW# | 23Mx25M | 44.19 | 0.19 | [48] |
GPU | ” Tesla K20 | 225 W (a) | CUDAlign 3.0 | 23Mx25M | 40.69 | 0.18 | [49] |
GPU | ” GeForce GTX 980 | 165 W (a) | SW# | 23Mx25M | 67.55 | 0.41 | [48] |
GPU | ” GeForce GTX 980 | 165 W (a) | CUDAlign 3.0 | 23Mx25M | 84.84 | 0.51 | [49] |
GPU | ” GeForce GTX 980 | 103.06 W | CUDAlign 4.0 | 51Mx50M | 112.71 | 1.09 | |
GPU | ” Titan X Maxwell | 189.00 W | CUDAlign 4.0 | 51Mx50M | 158.10 | 0.84 | |
GPU | ” Titan X Pascal | 193.96 W | CUDAlign 4.0 | 51Mx50M | 276.53 | 1.43 |