[RELEASE] cusignal v0.14 #109

GPUtester · 2020-05-28T15:36:41Z

❄️ Code freeze for `branch-0.14` and v0.14 release

What does this mean?

Only critical/hotfix level issues should be merged into branch-0.14 until release (merging of this PR).

What is the purpose of this PR?

Update documentation
Allow testing for the new release
Enable a means to merge branch-0.14 into master for the release

Realized I put my last change under 0.13 vs 0.14

…d fewer registers

[REVIEW] Fixed errors in test_wavelets and test_windows

While benchmarking modifications I noticed that the kernels actually got 30%-80% slower after refactorization. Upon further inspection, I realized I forgot to remove kernel.inpsect_types(), which I used to determine where additional register pressure was happening. After removal, kernel performance improved as expected. Pre-refactor ```bash ------------------------------------------------------------------------------------------------ benchmark 'Convolve2d': 18 tests ------------------------------------------------------------------------------------------------ Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- bench_convolve2d_gpu[valid-symm-5-256] 510.2240 (1.0) 15,333.3480 (26.26) 571.9330 (1.10) 383.8809 (79.14) 521.2340 (1.00) 9.3978 (2.20) 72;344 1,748.4564 (0.91) 1933 1 bench_convolve2d_gpu[valid-wrap-5-256] 511.6850 (1.00) 583.8680 (1.0) 519.9893 (1.0) 4.8505 (1.0) 519.4940 (1.0) 4.2635 (1.0) 275;59 1,923.1165 (1.0) 1935 1 bench_convolve2d_gpu[valid-fill-5-256] 511.8660 (1.00) 7,813.9960 (13.38) 572.2272 (1.10) 293.1461 (60.44) 520.5650 (1.00) 8.7820 (2.06) 90;369 1,747.5577 (0.91) 1935 1 bench_convolve2d_gpu[valid-symm-100-256] 513.9480 (1.01) 33,035.2710 (56.58) 1,526.7744 (2.94) 851.7301 (175.60) 1,680.8205 (3.24) 39.5810 (9.28) 305;477 654.9756 (0.34) 1930 1 bench_convolve2d_gpu[valid-fill-100-256] 514.1020 (1.01) 9,677.4270 (16.57) 1,552.3711 (2.99) 532.2713 (109.74) 1,665.1690 (3.21) 20.0863 (4.71) 365;555 644.1758 (0.33) 1923 1 bench_convolve2d_gpu[valid-wrap-100-256] 515.2980 (1.01) 26,289.8050 (45.03) 1,651.3394 (3.18) 937.2897 (193.24) 1,705.6270 (3.28) 358.8790 (84.17) 300;381 605.5690 (0.31) 1938 1 bench_convolve2d_gpu[full-fill-5-256] 635.2670 (1.25) 14,259.9010 (24.42) 713.8664 (1.37) 463.6417 (95.59) 647.1130 (1.25) 13.9065 (3.26) 59;225 1,400.8223 (0.73) 1517 1 bench_convolve2d_gpu[full-fill-100-256] 636.6020 (1.25) 44,891.0620 (76.89) 5,916.0973 (11.38) 2,463.1392 (507.81) 6,158.3765 (11.85) 58.7315 (13.78) 154;342 169.0304 (0.09) 1564 1 bench_convolve2d_gpu[same-fill-100-256] 646.5370 (1.27) 41,246.0190 (70.64) 3,118.7860 (6.00) 1,399.0277 (288.43) 3,270.7890 (6.30) 26.7110 (6.27) 166;400 320.6376 (0.17) 1536 1 bench_convolve2d_gpu[same-fill-5-256] 647.1240 (1.27) 21,469.7490 (36.77) 722.3554 (1.39) 613.8349 (126.55) 655.7870 (1.26) 12.7440 (2.99) 37;266 1,384.3602 (0.72) 1542 1 bench_convolve2d_gpu[full-wrap-5-256] 828.4980 (1.62) 1,444.1390 (2.47) 930.4144 (1.79) 67.3899 (13.89) 922.8130 (1.78) 10.0715 (2.36) 52;95 1,074.7899 (0.56) 1123 1 bench_convolve2d_gpu[full-symm-5-256] 830.2290 (1.63) 9,621.5270 (16.48) 1,013.7068 (1.95) 440.6848 (90.85) 925.5930 (1.78) 17.7040 (4.15) 61;230 986.4785 (0.51) 1103 1 bench_convolve2d_gpu[same-symm-5-256] 830.3560 (1.63) 1,363.4320 (2.34) 922.9753 (1.77) 29.2591 (6.03) 921.0910 (1.77) 10.2490 (2.40) 66;77 1,083.4526 (0.56) 1104 1 bench_convolve2d_gpu[same-wrap-5-256] 831.1370 (1.63) 5,935.4890 (10.17) 1,021.7239 (1.96) 369.6598 (76.21) 924.1815 (1.78) 20.7840 (4.87) 70;274 978.7380 (0.51) 1100 1 bench_convolve2d_gpu[same-wrap-100-256] 3,914.5930 (7.67) 10,156.3130 (17.39) 4,211.4239 (8.10) 479.8311 (98.92) 4,085.6320 (7.86) 66.1555 (15.52) 71;152 237.4494 (0.12) 1053 1 bench_convolve2d_gpu[same-symm-100-256] 3,930.4090 (7.70) 9,289.1910 (15.91) 4,269.3678 (8.21) 527.1550 (108.68) 4,128.2810 (7.95) 72.2638 (16.95) 79;138 234.2267 (0.12) 941 1 bench_convolve2d_gpu[full-wrap-100-256] 6,897.2370 (13.52) 31,018.7400 (53.13) 7,285.2016 (14.01) 1,174.7039 (242.18) 7,058.4005 (13.59) 20.6335 (4.84) 31;117 137.2646 (0.07) 552 1 bench_convolve2d_gpu[full-symm-100-256] 6,901.0070 (13.53) 39,261.4920 (67.24) 7,301.4274 (14.04) 1,379.2833 (284.36) 7,065.7780 (13.60) 13.0065 (3.05) 37;165 136.9595 (0.07) 843 1 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------ benchmark 'Correlate2d': 18 tests ------------------------------------------------------------------------------------------------ Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- bench_correlate2d_gpu[valid-wrap-5-256] 513.3330 (1.0) 17,201.1460 (30.09) 572.1528 (1.10) 451.9519 (117.45) 521.5820 (1.00) 7.3310 (1.73) 48;322 1,747.7848 (0.91) 1921 1 bench_correlate2d_gpu[valid-wrap-100-256] 513.4460 (1.00) 37,261.7010 (65.17) 1,520.8621 (2.91) 921.8817 (239.56) 1,673.4550 (3.21) 23.9982 (5.67) 283;494 657.5218 (0.34) 1929 1 bench_correlate2d_gpu[valid-fill-5-256] 514.3820 (1.00) 14,936.8660 (26.13) 574.0838 (1.10) 408.4802 (106.15) 523.4085 (1.00) 8.1730 (1.93) 53;297 1,741.9059 (0.91) 1922 1 bench_correlate2d_gpu[valid-symm-5-256] 514.4120 (1.00) 571.7280 (1.0) 521.7597 (1.0) 3.8482 (1.0) 521.3160 (1.0) 4.2300 (1.0) 431;46 1,916.5909 (1.0) 1922 1 bench_correlate2d_gpu[valid-symm-100-256] 515.2740 (1.00) 20,015.0360 (35.01) 1,535.0158 (2.94) 709.2960 (184.32) 1,677.6560 (3.22) 97.5280 (23.06) 325;500 651.4591 (0.34) 1922 1 bench_correlate2d_gpu[valid-fill-100-256] 516.8210 (1.01) 41,200.3440 (72.06) 1,529.9691 (2.93) 1,029.9279 (267.64) 1,667.2765 (3.20) 43.4215 (10.27) 7;484 653.6080 (0.34) 1920 1 bench_correlate2d_gpu[full-fill-5-256] 631.1470 (1.23) 8,252.6560 (14.43) 702.6754 (1.35) 358.7532 (93.23) 639.7100 (1.23) 7.5010 (1.77) 72;257 1,423.1322 (0.74) 1572 1 bench_correlate2d_gpu[full-fill-100-256] 637.2760 (1.24) 53,139.3930 (92.95) 6,167.4009 (11.82) 2,577.0833 (669.69) 6,376.5270 (12.23) 256.1610 (60.56) 166;282 162.1429 (0.08) 1558 1 bench_correlate2d_gpu[same-fill-5-256] 643.1740 (1.25) 17,520.5990 (30.64) 710.0926 (1.36) 506.4890 (131.62) 650.5470 (1.25) 7.5278 (1.78) 54;211 1,408.2671 (0.73) 1537 1 bench_correlate2d_gpu[same-fill-100-256] 646.7530 (1.26) 38,736.7920 (67.75) 3,195.6841 (6.12) 1,439.6151 (374.10) 3,341.2790 (6.41) 121.0445 (28.62) 164;246 312.9220 (0.16) 1528 1 bench_correlate2d_gpu[same-wrap-5-256] 827.2430 (1.61) 1,675.4340 (2.93) 921.2421 (1.77) 30.9059 (8.03) 921.5240 (1.77) 10.3455 (2.45) 43;61 1,085.4910 (0.57) 1105 1 bench_correlate2d_gpu[same-symm-5-256] 831.7930 (1.62) 12,938.7350 (22.63) 1,010.6727 (1.94) 615.6276 (159.98) 923.1270 (1.77) 15.2415 (3.60) 49;216 989.4400 (0.52) 1183 1 bench_correlate2d_gpu[full-wrap-5-256] 835.5890 (1.63) 1,329.2750 (2.33) 926.2752 (1.78) 27.9575 (7.27) 923.3630 (1.77) 11.7510 (2.78) 81;125 1,079.5928 (0.56) 1098 1 bench_correlate2d_gpu[full-symm-5-256] 842.3170 (1.64) 1,129.7000 (1.98) 928.5555 (1.78) 20.4641 (5.32) 924.8250 (1.77) 15.1653 (3.59) 178;91 1,076.9415 (0.56) 1125 1 bench_correlate2d_gpu[same-wrap-100-256] 3,852.3210 (7.50) 14,806.6290 (25.90) 4,268.0580 (8.18) 698.9350 (181.63) 4,127.3910 (7.92) 117.2280 (27.71) 56;106 234.2986 (0.12) 942 1 bench_correlate2d_gpu[same-symm-100-256] 3,859.9840 (7.52) 39,131.1580 (68.44) 4,311.6184 (8.26) 1,359.9556 (353.40) 4,153.8660 (7.97) 77.0693 (18.22) 17;132 231.9315 (0.12) 939 1 bench_correlate2d_gpu[full-symm-100-256] 6,945.8410 (13.53) 25,385.0130 (44.40) 7,533.7652 (14.44) 1,335.8629 (347.14) 7,288.2110 (13.98) 232.1215 (54.88) 38;83 132.7358 (0.07) 867 1 bench_correlate2d_gpu[full-wrap-100-256] 6,949.7780 (13.54) 13,981.4920 (24.45) 7,451.6177 (14.28) 606.5891 (157.63) 7,325.2910 (14.05) 117.3285 (27.74) 30;42 134.1990 (0.07) 399 1 ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ``` After refactor ```bash ------------------------------------------------------------------------------------------------ benchmark 'Convolve2d': 18 tests ------------------------------------------------------------------------------------------------ Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- bench_convolve2d_gpu[valid-symm-5-256] 289.3570 (1.0) 470.5760 (1.0) 299.8174 (1.0) 20.8994 (1.0) 294.0705 (1.0) 2.8040 (1.0) 255;429 3,335.3633 (1.0) 3390 1 bench_convolve2d_gpu[valid-fill-100-256] 291.0750 (1.01) 39,555.3130 (84.06) 1,718.1731 (5.73) 1,004.5103 (48.06) 1,798.2900 (6.12) 29.3343 (10.46) 348;758 582.0135 (0.17) 3383 1 bench_convolve2d_gpu[valid-wrap-5-256] 291.0810 (1.01) 6,733.8600 (14.31) 335.5837 (1.12) 203.8530 (9.75) 296.4200 (1.01) 11.2420 (4.01) 121;517 2,979.8823 (0.89) 3017 1 bench_convolve2d_gpu[valid-wrap-100-256] 291.3480 (1.01) 25,356.8570 (53.88) 1,713.2760 (5.71) 772.7803 (36.98) 1,802.1360 (6.13) 24.9540 (8.90) 351;792 583.6771 (0.17) 3351 1 bench_convolve2d_gpu[valid-symm-100-256] 291.6400 (1.01) 32,091.9010 (68.20) 1,761.0148 (5.87) 941.7382 (45.06) 1,845.2820 (6.27) 57.6167 (20.55) 356;617 567.8544 (0.17) 3393 1 bench_convolve2d_gpu[valid-fill-5-256] 292.7430 (1.01) 14,087.3250 (29.94) 332.3826 (1.11) 318.1229 (15.22) 302.8065 (1.03) 4.7920 (1.71) 32;545 3,008.5815 (0.90) 3314 1 bench_convolve2d_gpu[same-fill-5-256] 410.9540 (1.42) 637.5710 (1.35) 425.8010 (1.42) 28.7972 (1.38) 416.5360 (1.42) 4.4903 (1.60) 215;323 2,348.5152 (0.70) 2401 1 bench_convolve2d_gpu[same-fill-100-256] 412.5610 (1.43) 39,259.9070 (83.43) 3,695.8789 (12.33) 1,474.8376 (70.57) 3,790.8820 (12.89) 206.9310 (73.80) 214;295 270.5716 (0.08) 2409 1 bench_convolve2d_gpu[full-fill-5-256] 416.7480 (1.44) 31,754.1690 (67.48) 469.2916 (1.57) 682.8110 (32.67) 424.9395 (1.45) 8.4200 (3.00) 9;353 2,130.8715 (0.64) 2328 1 bench_convolve2d_gpu[full-fill-100-256] 417.5240 (1.44) 43,121.4420 (91.64) 6,389.9165 (21.31) 2,019.1906 (96.61) 6,549.3160 (22.27) 94.1055 (33.56) 192;335 156.4966 (0.05) 2379 1 bench_convolve2d_gpu[full-wrap-5-256] 603.8140 (2.09) 1,327.3670 (2.82) 615.6243 (2.05) 36.0608 (1.73) 610.3810 (2.08) 4.3390 (1.55) 30;142 1,624.3673 (0.49) 1622 1 bench_convolve2d_gpu[full-symm-5-256] 607.7200 (2.10) 14,550.7470 (30.92) 686.1686 (2.29) 455.0175 (21.77) 615.4170 (2.09) 11.5750 (4.13) 60;297 1,457.3677 (0.44) 1625 1 bench_convolve2d_gpu[same-wrap-5-256] 611.7380 (2.11) 21,033.0840 (44.70) 691.8494 (2.31) 578.4854 (27.68) 617.9800 (2.10) 10.9822 (3.92) 63;289 1,445.4012 (0.43) 1623 1 bench_convolve2d_gpu[same-symm-5-256] 612.7590 (2.12) 1,108.6150 (2.36) 633.4309 (2.11) 47.6948 (2.28) 619.7770 (2.11) 5.6733 (2.02) 83;264 1,578.7042 (0.47) 1555 1 bench_convolve2d_gpu[same-wrap-100-256] 3,912.4340 (13.52) 14,361.6620 (30.52) 4,531.6651 (15.11) 643.9760 (30.81) 4,430.3930 (15.07) 169.5663 (60.47) 75;136 220.6694 (0.07) 1191 1 bench_convolve2d_gpu[same-symm-100-256] 4,042.5770 (13.97) 19,196.8160 (40.79) 4,573.6260 (15.25) 803.4576 (38.44) 4,434.7250 (15.08) 137.1740 (48.92) 69;166 218.6449 (0.07) 1139 1 bench_convolve2d_gpu[full-symm-100-256] 7,063.3340 (24.41) 14,383.6150 (30.57) 7,544.1684 (25.16) 556.3906 (26.62) 7,407.1680 (25.19) 93.7680 (33.44) 82;142 132.5527 (0.04) 1087 1 bench_convolve2d_gpu[full-wrap-100-256] 7,186.3330 (24.84) 28,378.1610 (60.31) 7,583.5002 (25.29) 1,209.0888 (57.85) 7,365.3980 (25.05) 60.6180 (21.62) 25;116 131.8652 (0.04) 633 1 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------ benchmark 'Correlate2d': 18 tests ------------------------------------------------------------------------------------------------ Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- bench_correlate2d_gpu[valid-fill-5-256] 289.8440 (1.0) 469.2490 (1.0) 299.8807 (1.01) 20.0610 (3.50) 294.4315 (1.0) 2.7590 (1.27) 261;384 3,334.6590 (0.99) 3376 1 bench_correlate2d_gpu[valid-symm-5-256] 290.6350 (1.00) 543.3010 (1.16) 296.1015 (1.0) 5.7306 (1.0) 295.3565 (1.00) 2.1700 (1.0) 114;260 3,377.2201 (1.0) 3356 1 bench_correlate2d_gpu[valid-wrap-5-256] 293.2960 (1.01) 545.2400 (1.16) 303.2287 (1.02) 30.6294 (5.34) 297.6380 (1.01) 2.5895 (1.19) 65;335 3,297.8414 (0.98) 3340 1 bench_correlate2d_gpu[valid-symm-100-256] 293.7680 (1.01) 34,678.7460 (73.90) 1,922.7692 (6.49) 1,008.8000 (176.04) 2,024.8570 (6.88) 75.2370 (34.67) 318;716 520.0832 (0.15) 3366 1 bench_correlate2d_gpu[valid-fill-100-256] 294.4860 (1.02) 43,762.9800 (93.26) 1,883.7540 (6.36) 1,162.0444 (202.78) 1,968.9140 (6.69) 83.9130 (38.67) 326;575 530.8549 (0.16) 3366 1 bench_correlate2d_gpu[valid-wrap-100-256] 303.8300 (1.05) 29,100.6200 (62.02) 1,911.8953 (6.46) 867.0968 (151.31) 1,995.9900 (6.78) 78.4578 (36.16) 369;635 523.0412 (0.15) 3345 1 bench_correlate2d_gpu[full-fill-5-256] 416.1020 (1.44) 895.4670 (1.91) 428.3527 (1.45) 29.6915 (5.18) 420.9380 (1.43) 4.2977 (1.98) 133;282 2,334.5250 (0.69) 2369 1 bench_correlate2d_gpu[full-fill-100-256] 419.7600 (1.45) 48,226.9290 (102.77) 7,447.0345 (25.15) 2,322.9401 (405.35) 7,605.7280 (25.83) 332.8787 (153.40) 216;291 134.2816 (0.04) 2371 1 bench_correlate2d_gpu[same-fill-5-256] 421.1660 (1.45) 726.1020 (1.55) 428.4793 (1.45) 16.2861 (2.84) 426.4300 (1.45) 3.1037 (1.43) 37;170 2,333.8350 (0.69) 2359 1 bench_correlate2d_gpu[same-fill-100-256] 426.9120 (1.47) 50,810.3820 (108.28) 3,982.7944 (13.45) 1,843.8557 (321.75) 4,089.8880 (13.89) 156.3610 (72.06) 188;388 251.0800 (0.07) 2335 1 bench_correlate2d_gpu[full-symm-5-256] 599.7500 (2.07) 6,602.0830 (14.07) 674.0723 (2.28) 343.1494 (59.88) 607.2810 (2.06) 8.6010 (3.96) 68;328 1,483.5204 (0.44) 1656 1 bench_correlate2d_gpu[same-wrap-5-256] 603.1310 (2.08) 1,307.0180 (2.79) 631.8394 (2.13) 52.5475 (9.17) 608.7730 (2.07) 12.4580 (5.74) 255;268 1,582.6806 (0.47) 1642 1 bench_correlate2d_gpu[same-symm-5-256] 603.7990 (2.08) 6,925.6470 (14.76) 635.5537 (2.15) 261.9477 (45.71) 609.7730 (2.07) 3.3270 (1.53) 28;124 1,573.4311 (0.47) 1642 1 bench_correlate2d_gpu[full-wrap-5-256] 608.0400 (2.10) 13,025.6710 (27.76) 700.8097 (2.37) 476.8657 (83.21) 614.7330 (2.09) 65.0760 (29.99) 65;139 1,426.9209 (0.42) 1640 1 bench_correlate2d_gpu[same-wrap-100-256] 4,012.2520 (13.84) 28,239.4220 (60.18) 4,776.9270 (16.13) 851.5763 (148.60) 4,694.7670 (15.95) 156.2385 (72.00) 46;179 209.3396 (0.06) 1184 1 bench_correlate2d_gpu[same-symm-100-256] 4,045.4330 (13.96) 5,410.6700 (11.53) 4,509.4683 (15.23) 242.4697 (42.31) 4,502.0000 (15.29) 258.9298 (119.32) 96;7 221.7556 (0.07) 305 1 bench_correlate2d_gpu[full-wrap-100-256] 7,441.9810 (25.68) 42,325.2290 (90.20) 8,601.1267 (29.05) 1,244.4556 (217.16) 8,476.3290 (28.79) 333.7595 (153.81) 46;136 116.2638 (0.03) 1101 1 bench_correlate2d_gpu[full-symm-100-256] 7,652.4150 (26.40) 26,369.2740 (56.19) 8,595.7713 (29.03) 1,025.7598 (179.00) 8,428.3790 (28.63) 307.3635 (141.64) 75;120 116.3363 (0.03) 1241 1 ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ```

[REVIEW] Branch 0.14 merge 0.13

[REVIEW] Refactor _signaltools.py to new Numba/CuPy framework.

Added `import pytest-benchmark`

Install pytest-benchmark for CI process

Removing pytest-benchmark

[REVIEW] Add pytest-benchmark to cuSignal library

…_numba for correlate2d and convolve2d 2. Update _signaltools.py to now use cupy.pad(symm/wrap) versus numpy.pad(symm/wrap) 20x-30x improvement elminiating data transfers 3. Update Numba kernel indexing to match CuPy raw kernels

[REVIEW] Added CuPy raw kernels for correlate2d and convolve2d

[REVIEW] Port to CuPy

[REVIEW] Fix flake8 errors

[REVIEW] Reorganize Jupyter notebooks to match code reorg

[WIP] Implementation of `sosfilt` as an alternative to `lfilter`

mnicely · 2020-05-28T15:44:25Z

README.md

+## Documentation
+The complete cuSignal API documentation including a complete list of functionality and examples can be found for both the Stable and Nightly (Experimental) releases.
+
+[cuSignal 0.13 API](https://docs.rapids.ai/api/cusignal/stable/) | [cuSignal 0.14 Nightly](https://docs.rapids.ai/api/cusignal/nightly/)


Should this be cuSignal 0.14 API and cuSignal 0.15 Nightly?

mnicely · 2020-05-28T15:45:07Z

README.md

+```
+# For CUDA 10.0
+conda install -c rapidsai -c nvidia -c conda-forge \
+    -c defaults cusignal=0.13 python=3.6 cudatoolkit=10.0


Again, should this be cusignal=0.14?

mnicely · 2020-05-28T15:45:28Z

README.md

+
+# or, for CUDA 10.1.2
+conda install -c rapidsai -c nvidia -c numba -c conda-forge \
+    cusignal=0.13 python=3.6 cudatoolkit=10.1


cusignal=0.14?

mnicely · 2020-05-28T15:45:29Z

README.md

+
+# or, for CUDA 10.2
+conda install -c rapidsai -c nvidia -c numba -c conda-forge \
+    cusignal=0.13 python=3.6 cudatoolkit=10.2


cusignal=0.14?

mnicely · 2020-05-28T15:46:07Z

README.md


 1. Clone the repository

    ```bash
-    # Set the location to cuSignal in an environment variable CUSIGNAL_HOME
+    # Set the localtion to cuSignal in an environment variable CUSIGNAL_HOME


localtion --> location?

mnicely · 2020-05-28T15:47:36Z

README.md

@@ -261,9 +316,48 @@ In the cuSignal top level directory:
    pytest
    ```

+### Docker - All RAPIDS Libraries, including cuSignal
+
+For `cusignal version == 0.13`:


0.13 --> 0.14

mnicely

Most of my comments are about versioning.

awthomp · 2020-05-28T16:32:59Z

I concur with all of Matt's suggestions. @BradReesWork, how do we go about updating the README w.r.t. this Release PR?

raydouglass · 2020-05-28T16:37:18Z

how do we go about updating the README w.r.t. this Release PR?

Open a PR against branch-0.14 and notify me for approval to merge it.

awthomp · 2020-05-28T19:21:44Z

@raydouglass -- Pushed README update here: #110

[REVIEW] Update readme for 0.14

mnicely and others added 30 commits April 2, 2020 13:30

Update CHANGELOG.md

c106bd4

Realized I put my last change under 0.13 vs 0.14

Converted numba kernels to use new framework, type specialization, an…

f4da5e0

…d fewer registers

Update CHANGELOG.md

9c27ab2

Merge pull request #44 from mnicely/fix_tests

1c118c5

[REVIEW] Fixed errors in test_wavelets and test_windows

Merge branch-0.13 into branch-0.14

fb0d64e

Merge pull request #46 from BradReesWork/branch-0.14-merge-0.13

f5db3ab

[REVIEW] Branch 0.14 merge 0.13

This should fix an unintended push/merge

0e604d4

Added cupy raw kernels for correlate2d and convolve2d

39a6552

Addition of decimation for FIR ftypes

ab77c42

Fixing PR number

9411a07

Merge pull request #45 from mnicely/correlate_convolve_2d_numba

9ec3f55

[REVIEW] Refactor _signaltools.py to new Numba/CuPy framework.

Update bench_windows.py

ba173af

Added `import pytest-benchmark`

Update bench_wavelets.py

03923e6

Added `import pytest-benchmark`

Update bench_waveforms.py

c99448e

Added `import pytest-benchmark`

Update bench_spectral.py

7760c51

Added `import pytest-benchmark`

Update bench_signaltools.py

aef7e71

Added `import pytest-benchmark`

Update build.sh

ab00a4d

Install pytest-benchmark for CI process

Update bench_signaltools.py

fabbff9

Removing pytest-benchmark

Update bench_spectral.py

e639cd2

Removing pytest-benchmark

Update bench_waveforms.py

0afc17b

Removing pytest-benchmark

Update bench_wavelets.py

edc8267

Removing pytest-benchmark

Update bench_windows.py

4431c15

Removing pytest-benchmark

Merge pull request #43 from mnicely/pytest_benchmark

2bcf5df

[REVIEW] Add pytest-benchmark to cuSignal library

Merge branch 'branch-0.14' into decimate

1032ac4

Merge branch 'branch-0.14' into correlate_convolve_2d_cupy

a247c41

Update CHANGELOG.md

d556c64

Fix flake8 issue

47512b3

Merge pull request #49 from mnicely/correlate_convolve_2d_cupy

3578fcf

[REVIEW] Added CuPy raw kernels for correlate2d and convolve2d

mnicely and others added 14 commits May 15, 2020 09:58

Ported Numba kernel to CuPy

0d6cd5e

Clean up

353f9fb

Merge pull request #2 from mnicely/awthomp/sosfilt

530b199

[REVIEW] Port to CuPy

Reorganize jupyter notebooks

f9af927

Update PR number

d4c4c9e

fix flake8 errors

abd7455

update changelog

75af420

Fix ambigous variables

b10725b

Add extra line

c899ee9

Merge pull request #104 from awthomp/flake8_fix

fd282ab

[REVIEW] Fix flake8 errors

Merge pull request #103 from awthomp/notebook_reorg

14829e3

[REVIEW] Reorganize Jupyter notebooks to match code reorg

Fix pytest error

2a4bfa9

Place warning on experimental API in sosfilt docs

9d60d70

Merge pull request #99 from awthomp/sosfilt

110b8c8

[WIP] Implementation of `sosfilt` as an alternative to `lfilter`

GPUtester requested review from a team as code owners May 28, 2020 15:36

mnicely reviewed May 28, 2020

View reviewed changes

Update readme for 0.14

5f47852

raydouglass added 2 commits May 28, 2020 15:27

Merge pull request #110 from awthomp/readme_update

a39e955

[REVIEW] Update readme for 0.14

Update CHANGELOG.md

0adcf46

raydouglass merged commit 8a8976e into master Jun 3, 2020

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

[RELEASE] cusignal v0.14 #109

[RELEASE] cusignal v0.14 #109

GPUtester commented May 28, 2020

mnicely May 28, 2020

mnicely May 28, 2020

mnicely May 28, 2020

mnicely May 28, 2020

mnicely May 28, 2020

mnicely May 28, 2020

mnicely left a comment

awthomp commented May 28, 2020

raydouglass commented May 28, 2020

awthomp commented May 28, 2020

[RELEASE] cusignal v0.14 #109

[RELEASE] cusignal v0.14 #109

Conversation

GPUtester commented May 28, 2020

❄️ Code freeze for branch-0.14 and v0.14 release

What does this mean?

What is the purpose of this PR?

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely May 28, 2020

Choose a reason for hiding this comment

mnicely left a comment

Choose a reason for hiding this comment

awthomp commented May 28, 2020

raydouglass commented May 28, 2020

awthomp commented May 28, 2020

❄️ Code freeze for `branch-0.14` and v0.14 release