mpw-006 / DNM Deep N-Well

the DNM shapes of all of mpw-006

40 of 40 dies rendered.

20,279 shapes in total, each die at 0.125 µm per pixel.

result.json · job.json · reticle overview PNG

1234567
A A1 A2 A3 A4 A5 A6
B B1 B2 B3 B4 B5 B6 B7
C C1 C2 C3 C4 C6 C7
D D1 D2 D3 D4 D5 D6 D7
E E1 E2 E3 E4 E5 E6 E7
F F1 F2 F3 F4 F5 F6 F7

Downloading the full-resolution image

The stitched reticle is 53,432×65,056 pixels — 3.48 gigapixels. The file itself is small, but decoding it needs about 3.5 GB of memory however small the file is, and most viewers refuse it outright. So it is also published as 42 tiles of about 7576×10776 px (4.7 MB in total, largest 120.4 kB), cut in the gaps between dies so that every tile holds whole projects and none is split.

To put the full-resolution PNG back together from them, byte for byte, with nothing installed but Python itself:

python3 reconstruct_reticle.py

Run it in a directory holding the tiles and mpw-006_DNM_tiles.json and it finds them itself, checks every tile against its checksum as it reads it, and checks the finished file against the manifest. It works because the tiles and the full image are written with PNG's Up filter, which never looks at the pixel to its left — so a row of tiles' scanlines laid end to end is the full image's scanline, and rebuilding moves bytes rather than doing pixel arithmetic.

Whole-reticle files

FileSizeMD5SHA-1SHA-256
mpw-006_DNM_reticle.png
the stitched reticle, full resolution
3.7 MB 9c37eda42eb3f5d752e521c22747540848acca9f241fb81c5dc34a74786df13cda8eb142 d17a08aa91057ebda9428ff09f232c0dcff79e79bbde2efea215cf657e3df6d2
mpw-006_DNM_reticle_overview.png
the same image scaled to fit 4096 px
186.4 kB 063bf46b9a0c42b7a4773af972d6d6e1edcf495bec182af766440dd79fb17895537bce88 81108fc6a60b475f1fa4a369227eafb3961fc5568cb1d74123b222fd29d12e50
mpw-006_DNM_tiles.json
where every tile belongs, and its checksum
13.6 kB 3f72a61f4ea292d06c203daefec958316208cf19df4e2bc01dca5adacf3600dfca827f7b d8376df6a31251cbd283da8a2d7d6419c73f244919e1e35353ec143896ae6315
reconstruct_reticle.py
rebuilds the reticle from the tiles, standard library only
11.9 kB 4406f1f3db8a4a85756610b7c432c47a294714566ceb084187594ced0020f9260faac32a d2e72bf4b2541f1a8acb11eb758917c5b5fa080b41b3a7118487c03f8af2a769

Every file in this directory is listed in MD5SUMS · SHA1SUMS · SHA256SUMS, in the format the standard tools read:

sha256sum -c SHA256SUMS

The 42 tiles

FrameProjectPixelsPositionSizeSHA-256
A1 free_and_open_source_silicon_implementation_of_aes 7576×107760, 0 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
A2 microwatt_mpw6 7576×107767576, 0 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
A3 hack_soc_-_mpw-6 7576×1077615152, 0 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
A4 riscduino-dcore_d3_ 7576×1077622728, 0 112.5 kB3ce3c51e59a1c06ab697c7e03edcdf850f604c8cff2d7a9d5cbb82b4c8e6009c
A5 riscduino-qcore_q2_ 7576×1077630304, 0 112.5 kB3ce3c51e59a1c06ab697c7e03edcdf850f604c8cff2d7a9d5cbb82b4c8e6009c
A6 riscduino-score-s4-2 7576×1077637880, 0 112.5 kB3ce3c51e59a1c06ab697c7e03edcdf850f604c8cff2d7a9d5cbb82b4c8e6009c
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
B2 ft8_receiver_test 7576×107767576, 10776 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
B3 azadi_iii_dft 7576×1077615152, 10776 112.6 kBeec4280521bc470ef54dc131f16cabdfbb10ffd1150defbffd61cfcc289af532
B4 sramtestvehiclesequel 7576×1077622728, 10776 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 112.5 kB2a9211b0d5ebf4bd82621734b612e90b3429dd8f18bb2c833b169d881df9dca7
B6 asicle-ro 7576×1077637880, 10776 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
B7 10b_adc_and_analog_support 7976×1077645456, 10776 115.5 kB559fb2e40c49b63efb3a554480fc638b3fc2a035d8fb0f4ce88ecf60e06e67c2
C1 yonga-modbus_controller 7576×107760, 21552 112.4 kB2e463061705a631f474ccf803d535f9074ad3d21c83bf9f1ac6650dfdaef1ef6
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
C3 openram_test_design 7576×1077615152, 21552 112.5 kB4055f128537aa986fe70c73b93a5593ee8d62452f156abcf3fb9b5167087fdc0
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 116.4 kB91ed4fda16a2fc3babb16324fd02d00989912def40f6db0febd7e6ecf0ebe6af
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
D3 order_prga_mpw6 7576×1077615152, 32328 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 112.4 kB6c9a3611ff805a06f8d2632092819acd19097027a89497cd3ed5566ec0e01751
D5 large_memory_micro 7576×1077630304, 32328 112.6 kB83e91b604872c34ff303732f9295697fe4a3179706f9b74d35c06f17cbcd2687
D6 rng_chaos_scroll 7576×1077637880, 32328 112.4 kBd33c8014c5fdbadbb3282c9ff7ebcddd13e6456753cc8cb760ab2a8e9508d49d
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 115.5 kB559fb2e40c49b63efb3a554480fc638b3fc2a035d8fb0f4ce88ecf60e06e67c2
E1 mixed_signal_circuits_v2 7576×107760, 43104 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 111.4 kB23348fb20943bcaa3695e06365748802690992ff4eb3b4ecebd981daffdd8f3d
E3 floating_point_halfprecision 7576×1077615152, 43104 112.4 kBe8034c485c9297d7c991967bb71c41a90a90d04224246ed3a35b6b3153e8d8cb
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 112.4 kB04d7679a299a2fb21824f129cd63a38f7a16bbf303d6c8310681793558760120
E5 floating_point_unit_single_precision 7576×1077630304, 43104 112.4 kB4dd953e18984f82a5cd13b2198172b2ac00a697b6690acef927735e54e099477
E6 experiar_soc 7576×1077637880, 43104 112.7 kBeeb7e93971a08f0ff2c3c62d234d9a2ef0ce2eabedf4c031542bfce144b2441f
E7 my_caravel_analog_project 7976×1077645456, 43104 115.5 kB559fb2e40c49b63efb3a554480fc638b3fc2a035d8fb0f4ce88ecf60e06e67c2
F1 efabless_mpw6_riscduino 7576×111760, 53880 116.2 kBff6116af427f2e7e46f42361e94359f4c9ed8cdd9f098dc9750a0720f9159904
F2 motius_pong 7576×111767576, 53880 116.2 kBff6116af427f2e7e46f42361e94359f4c9ed8cdd9f098dc9750a0720f9159904
F3 soc_now 7576×1117615152, 53880 116.3 kBbbe2a9939b29581dff6f6cd98d798d9fb6c2bd3ef2ae74b07bfca5416f1b3910
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 116.2 kBff6116af427f2e7e46f42361e94359f4c9ed8cdd9f098dc9750a0720f9159904
F5 optimised_strong_arm_latch 7576×1117630304, 53880 115.2 kB1c229a258e14d5ab7557ba36ec7c01b1a43a0029797590574bed9e1fef8e8758
F6 riscduino_qcore_folk 7576×1117637880, 53880 116.3 kBcdd38fca2caa1dbe2a2342f0fc4e262d0136322ca7acabd02935da6a5117d860
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 120.4 kBb1ceae9b8122c0cb057b22c98da91a79821777268d6ef793ade0f34d2c2a7871

Position is the tile's top-left corner in the full-resolution image. MD5 and SHA-1 for the same files are in the checksum files linked above.

About DNM on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask DNM

Mask layer
DNM — Deep N-Well
Process step
7 — Deep N-well mask
Drawn layer
64:18
Layer on the mask-layer GDS
48:0
Detail
DNM = dnwell sized by cdnm.3
Used in SKY130
yes

mpw-006 — SKY130 MPW-6

Foundry product
EF MPW#6 (+ 'With ReRAM' split lot)
Reticle set
5CS8014AC
Run date
2022-04-11
Submissions closed
2022-06-08
Projects
85
Fab lot
Identification
confirmed — Lot records: EF MPW#6 ('Held pre-mask' in late 2022; MPW-6 taped out 2022-12)
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-6 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-006/foundry

These are renders of the drawn shapes that go on each photomask, taken from the layouts the shuttle's projects taped out — they are not photomask artwork: reticle pitch, the 4x reduction, mirroring and the frame features the fab adds are not modelled. An empty image is a real result; several mask layers are used by no project on a given shuttle. Each die's source layout is named in result.json and lives in the public shuttle repositories under foss-eda-tools.googlesource.com, so every image here can be traced back to the tape-out it came from. Generated with sky130-mask-decoder.