mpw-006 / MM2 Metal 2

the MM2 shapes of all of mpw-006

40 of 40 dies rendered.

513,210,835 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 (536.2 MB in total, largest 20.7 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_MM2_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_MM2_reticle.png
the stitched reticle, full resolution
253.7 MB cc98631bb2e4eb3448428bd7b72319de32b38419f4d3e390b07d574772cd2c501ce3c040 9c807c4fdff5d7d3be977f0013571fd93c8291a58670e536cdeecbff69903691
mpw-006_MM2_reticle_overview.png
the same image scaled to fit 4096 px
5.8 MB 9bf62bf4d97b59c6f8caf6751ce4024a0ac2a410433a2544b69950f0dd64355a5f2f377f 11891209a0619ad3c362b0fe9ff99ed7587b96b2d81ccb67dc21664d36c60647
mpw-006_MM2_tiles.json
where every tile belongs, and its checksum
13.6 kB 592017d167d3c6c0b9fa20aeed800e30a6d31113e2b81efda4896ba4dfc7156270570920 2156802d28d05affd2ca4a0df4377d01cc9a686feef7798ace09729766065a9b
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 12.3 MB81e15b50dd68d9613b3602b9594a101cc59a11248dedd81abaf3d1eb3e97370b
A2 microwatt_mpw6 7576×107767576, 0 20.3 MBca9595409ce003a8858a0a71821553faa64d3ccac28ec2b5156c38674b0356f0
A3 hack_soc_-_mpw-6 7576×1077615152, 0 12.3 MBde2a5da6cdf40d6beb20ee5079522cd5ea362f48a498de5dcd17811086f23adb
A4 riscduino-dcore_d3_ 7576×1077622728, 0 17.2 MBf0533fb946106058caeeb81141e1d7f72ec54ef8ba0ea5149012d13a7259cbb6
A5 riscduino-qcore_q2_ 7576×1077630304, 0 18.7 MB913318b91d0cf97a0ec90cfa6f5480cb8b3ee37c30586521bea32638cd447c13
A6 riscduino-score-s4-2 7576×1077637880, 0 16.4 MB7a130e8ce66d3e3037091a176619fb1a7d9411edf46a2fd58cb9a913fa92e7d3
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 15.2 MB6c2236d626a2c4c716cb345f443643025f428d4195399d9b834c803cfff9bb57
B2 ft8_receiver_test 7576×107767576, 10776 8.2 MBd3779962ca25af9fae2dec16d2e598e65bf8d392b77c8fd9b09176b4e432eb41
B3 azadi_iii_dft 7576×1077615152, 10776 14.5 MB7081c7ba20d15b1720c71ca3acb2cf9f6de28d381ff19b01aaf63207cff295e8
B4 sramtestvehiclesequel 7576×1077622728, 10776 8.9 MBb39b0d766ad2d54206a486ae52bb7c6a3a4d23391d7ce5b57a68692693c072ad
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 16.4 MB1dcf337dee8ec710262a22adc1ca1418d85a1e59410df73a72012f9fe22dfc83
B6 asicle-ro 7576×1077637880, 10776 15.5 MB855d39150a2a48ddf84fe4239afa912d0eb522853fbf40f4d3425b55f8654608
B7 10b_adc_and_analog_support 7976×1077645456, 10776 8.9 MB728e0cd4f2b1692d13d5a7adde49623da15f5f829e4b3ca6a80fcf78d7ac50d4
C1 yonga-modbus_controller 7576×107760, 21552 12.0 MBfce74b774a2292c11ec2f1d712c72eb85c6e3ed93d910bff7ad606b54fc33823
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 12.7 MB43a89f32aa57e39d8a8dccb2f2bafbd85d90008244c3c01b1f793950004b4058
C3 openram_test_design 7576×1077615152, 21552 12.9 MBd1148a4666811fafa2ffc122e4533b156c4f61494f34d08889baaa197c163f72
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 15.5 MBfae82e74851a2198b976d0f2b1c9f06d0d0ba39f105242412fde9b5206f1f3be
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 12.6 MBd8f6629863601de221e623c95a2e0db500cca44d241e7f8d286804a11d6f2512
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 10.9 MB7445199feaa9a4cf4c7f1d1a93e148ae1ed0301287b35cb1a06eab62f8bcdc92
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 8.1 MB0f74011a9060386dea2fe7897a482ede3291b154dafa31c0038bdb964aee0d6a
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 8.1 MB9a9186c7c8ebbda9b435568130ce003bb74933dccf899f539afff7d20ca7c837
D3 order_prga_mpw6 7576×1077615152, 32328 20.7 MB0c4af60176cf574fb91e9ced2cfc6fc42997facc1449811f06db62a2dbf559a5
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 9.7 MBe6d343f59cdac0d404090534a43d4ca913f750597d6bb1fd59773de020ad8127
D5 large_memory_micro 7576×1077630304, 32328 18.4 MBf40176b412a00f42d8ac0ae176872339092fd61b82c4bfe4e0088af1def67a7b
D6 rng_chaos_scroll 7576×1077637880, 32328 13.1 MBa90759ebe1c8196ad0bef3893269519012f6cf342152d1f50caa5bb73e82fd0a
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 8.4 MB14742079755f524ae044e900be809558aaac22cc5d670b221cbc7419727c1946
E1 mixed_signal_circuits_v2 7576×107760, 43104 8.2 MB542e5bf5efa1a8de682fef62aab4c005aaf88de90e84bb8b5a34ad81bef486fa
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 8.1 MB1816421eef9052f62ba1e32c4f7e762250a3ea0413f68ca0729f1b883a5a209d
E3 floating_point_halfprecision 7576×1077615152, 43104 14.1 MB05e816e195c770dc342c4d3bcd5af54d6e817f13467c1b79fee2ec0b008aefc1
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 16.1 MBf0da1d620f4984a4b64fb68a9369c65ed1d33201ecd27b78b4f8c3def7cf291e
E5 floating_point_unit_single_precision 7576×1077630304, 43104 16.4 MB2d3050efbfefe49c4b2bd12c233c15376303996770d638901488285483f483c3
E6 experiar_soc 7576×1077637880, 43104 17.1 MBd2f9652edeb646fcb83a3dafa8106aba310d4ad69e13df4eeb332172641f8a72
E7 my_caravel_analog_project 7976×1077645456, 43104 8.2 MB91f2832cb787663291360153c086e3c96c97efa46b725ec7ed067491dd595de5
F1 efabless_mpw6_riscduino 7576×111760, 53880 19.6 MBa5f8e0e80a405dc6e5e0170dc9262e966aa1bc380ba02fdec25dd287a77f095f
F2 motius_pong 7576×111767576, 53880 10.0 MB28d4a919357080fa62f7c2c65de9383806771ac441c0ae7cf497f76269b1f472
F3 soc_now 7576×1117615152, 53880 11.3 MBe1a5026699d72b06a4b2f0335eaba9d6269527403ae0067547fef9698bd12fc7
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 20.7 MBfbb68bee2547f3cfb3b415e2a917d493406bd8dd4a183b0df16d0e3e59849eee
F5 optimised_strong_arm_latch 7576×1117630304, 53880 8.1 MB4a87d3964972841cc549c26d6c4b9e81de42b2a2903fdaec150545e4416e7e30
F6 riscduino_qcore_folk 7576×1117637880, 53880 18.2 MB2df74150823b151d82f5e9b88867e70b4f158ef64420727b18988d1e4046e464
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 12.3 MB9ee8a21851c20a8b775dc1db70734ddec894885f29866320683b27fcdd7aea1a

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 MM2 on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask MM2

Mask layer
MM2 — Metal 2
Process step
124 — Metal mask2
Drawn layer
69:20
Layer on the mask-layer GDS
41:0
Fill layer
41:28
Also
Metal 2
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.