mpw-006 / NPCM Nitride Poly Cut

the NPCM shapes of all of mpw-006

40 of 40 dies rendered.

21,643,346 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 (96.2 MB in total, largest 4.7 MB), 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_NPCM_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_NPCM_reticle.png
the stitched reticle, full resolution
72.9 MB 829d6397592fdbba352be2d9168f7f8f7eb57796194798697f7a3b065de75d4a3e99940d 7346cbaa511e6fa17c351dadeb8a767f358cc2009b5534903371902ed6482dbd
mpw-006_NPCM_reticle_overview.png
the same image scaled to fit 4096 px
2.3 MB 817c24e503f43bb26fcf18b00b93e1132de721edf161296bdc11a95429fb38b0f35afe72 425a5eeb64fc1f34729f91b5b03f305a1367a53281629c738f7324ac47f78af4
mpw-006_NPCM_tiles.json
where every tile belongs, and its checksum
13.7 kB 7a71db2500729f5f7eddd3e70c8614f2af3683a9956d4a0927392b5def219c04ba4191d1 9bc70d32423b198e1be85deec9afbc677fe69ac8dcdf313704dbad2b8835e4a8
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 1.8 MB899f83b0f32c8c0594df5ab90cba36b84c22dde55e8b2e52c86f1b029e9b7cfb
A2 microwatt_mpw6 7576×107767576, 0 4.5 MB61f2084a0769e8e8b7c728ef143bf73a6e0cdd950a6e9e2f25d74f87484d3d6f
A3 hack_soc_-_mpw-6 7576×1077615152, 0 1.6 MB88cf7a629995cc13db8ed10da8c6392f7c626126c7e72d9b32fa5c4db69dae7c
A4 riscduino-dcore_d3_ 7576×1077622728, 0 3.9 MB0c468d7f9826f8725c6720f06d6f0b73376428fe18ef452950e9d31100a76925
A5 riscduino-qcore_q2_ 7576×1077630304, 0 4.7 MB279205f6ac1ed015866f352b4396b3a91b264c086ca642b2c6241247daaf0b77
A6 riscduino-score-s4-2 7576×1077637880, 0 3.6 MB97ecb63c3daa1939afdbf50b712e97ecd47e577648629314584cb6d305ed2674
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 2.9 MBa95a6201a412e3cff5e5227cc547515d6628fce287f77aef6ec2865437adc154
B2 ft8_receiver_test 7576×107767576, 10776 1.5 MB1b6a3408a55f1c660409097b25a800e7862e8b075bd05b43922ba54c12e8bd7f
B3 azadi_iii_dft 7576×1077615152, 10776 2.8 MB368f18fbd8b930e26ad33c45371cbcea1c78c2e443a7ea994c65812673b899e5
B4 sramtestvehiclesequel 7576×1077622728, 10776 1.5 MB46e27b967cc3c47bb1b7145763edebb63d01fb1de24989d227a9de574078a0c9
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 1.8 MBc2a41109fbbea7b9d20b9d38f487cdd489db13861f1f97e8761752fc11c2f32a
B6 asicle-ro 7576×1077637880, 10776 2.5 MB6ce36c2e8ed3a925378cc2e89e2919ae3778b3fd44462562f0048024799cc0cf
B7 10b_adc_and_analog_support 7976×1077645456, 10776 1.6 MB9a40cf1382c97d857d075a4bfd30cdbfea729a3d8813aa5b29b5fd8f22f82dd6
C1 yonga-modbus_controller 7576×107760, 21552 1.8 MBff0ce1ce9080353aea4f02baae80abca303abc39e5c725721368f851d8a27365
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 1.9 MB3f6c227e5d4f7546f6b0cc949be7a5b1b376c33319cab9643f4d7641ea06ceaf
C3 openram_test_design 7576×1077615152, 21552 2.1 MB56da0c421851f3699d1485dc9e4a9315847e731c5bb772edf0b27b33b4699852
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 2.0 MB49cff6d8ebde4af3ebbd0be70ef51a657511342670f16296cc015af1e0ebdf16
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 1.7 MB2d3c546e1265ee5e9f22c0cc2bb3b3676275e273a7bb0f7d589b1b095f3c4577
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 2.1 MB7aa7fe5792ed0e8d2aeefc57beb801ba1b8318eb726706c2919daef496f2e06f
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 1.5 MB937feea50d04b430b62dac1b3c757b33d66d8d8bb5d530906722707ee47b4bde
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 1.6 MBaa7e7cb48bb3cd87161b9ccc2a32089c0193f2cefbdfe33bb73dba1252d257a1
D3 order_prga_mpw6 7576×1077615152, 32328 4.3 MBedcae98071d9ea1d034081ee29281acf69fee1ec0702e4928c6609827a0aa2a2
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 1.8 MB2744c5a99b2a709403eebc312fb480ddf0f3e774b35bcae89725924f91a47327
D5 large_memory_micro 7576×1077630304, 32328 3.6 MB7a1f774706f9ae3126b3a1e21a020234280852212ef370e8148adf66ad2a9250
D6 rng_chaos_scroll 7576×1077637880, 32328 1.8 MBacabd0c36f9c88f1cebd8fa230f6a83ec3519dcd04cbbcd0fd85fcf0423fd958
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 1.5 MBaf077d5970ea076703fa107ac59c41149fdf78a491f4ee27cc9a7108b4662c3c
E1 mixed_signal_circuits_v2 7576×107760, 43104 1.6 MB41c9e079b1578d8b7486dabd041d4e8ffd3f340855453c639bbe4c520a076aa1
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 1.5 MB7bf8fe2eb7ded9e78597c2e191b7bfd6e749c3cc00a908ad8a257a3d21c16354
E3 floating_point_halfprecision 7576×1077615152, 43104 1.9 MB3710ee4f30d0b4d769c9330933aee9857365e715741d25b7a6b1881a1911e5f9
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 1.9 MB5feecf7dc7fa9814412aca995e7b7d95d1bd128c8137a30d80d7df4328f2c8e1
E5 floating_point_unit_single_precision 7576×1077630304, 43104 2.0 MB35164e8d6e551b3b197a9608b5e3ff599a3f9e00571d68da8da3fd14e5010c00
E6 experiar_soc 7576×1077637880, 43104 3.1 MBdd07318297616f47f184e0a2a0ff2a7dd5b90ab7f6f51ba44f50ae478e244e68
E7 my_caravel_analog_project 7976×1077645456, 43104 1.5 MB4ac81c801b85b7bd14ded4cbda99cb4b64f2fce90c172e0ec89318f6cb6f0676
F1 efabless_mpw6_riscduino 7576×111760, 53880 4.6 MBe3f5fe43063c6357b5e9584a6cff8c080aacb81e9da65ea847fad3adde25354e
F2 motius_pong 7576×111767576, 53880 1.7 MB69cf10a5aeef6fd32aa928cd1dafef2b50b355b2ce6f246f730716cf0d9c2236
F3 soc_now 7576×1117615152, 53880 1.9 MB1f024d428f99e3f165f13095dfc971de280b40e8824093be2f7e36b74e8b4d2c
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 4.3 MBb52c41dca22519ad980719381faaefbebc98464709e6cc264f1c5dfa00831ec0
F5 optimised_strong_arm_latch 7576×1117630304, 53880 1.5 MB0990c151cd8c4133eb9948bb3deba1e0779307bbea767a8c30f1258e4777f3a5
F6 riscduino_qcore_folk 7576×1117637880, 53880 4.5 MBbf2b0027dd25d1a2b2a80361c4e9148e4c69a45c97b95cadc45b77a4a104d5a9
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 1.6 MB739140408075f3cd98117810ec947b6ce8346d948d00f400fe187c03136299c0

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 NPCM on mpw-006

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

Mask layer
NPCM — Nitride Poly Cut
Process step
78 — Nitride poly cut mask
Drawn layer
95:20
Layer on the mask-layer GDS
49:0
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.