mpw-006 / FOM Field Oxide

the FOM shapes of all of mpw-006

40 of 40 dies rendered.

87,978,218 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 (214.5 MB in total, largest 10.0 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_FOM_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_FOM_reticle.png
the stitched reticle, full resolution
161.2 MB 4230ad9e4ff4b2a494d3795fbe75175132c0518cd989b6fe3fe661ae59ceb4517262f091 44f17aa8ab1ff8384b18ff8be7ca900571c25ffd61afdf9b36fac7d896741b32
mpw-006_FOM_reticle_overview.png
the same image scaled to fit 4096 px
8.2 MB c0321e72fb9de79e6b3c83c232a71440e78ad1e279fa294ae7d33f466183fa0db6549386 ad9b1cd7c96d115d9290a4cb62ac9fdc60893ab0b17fa4fc994e4c6f6d2ba7b3
mpw-006_FOM_tiles.json
where every tile belongs, and its checksum
13.6 kB 653f007cb78f147bd363332a7967cb41085bebd1a8fcb5a7452702b3bbf49a61fce6739b e8cdd92b804d5c9abba7609170ccbecd321d539a453ee61c91fad25069ed6e26
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 4.1 MBc66f4e02a5f128ec558964c7f1d9fecf9df9910a53516dc47e50e0bb90146e80
A2 microwatt_mpw6 7576×107767576, 0 9.6 MB21b804efda11bf3eedc4e8d0d15d3960b4debadb39cb08e03ad5884505deeed3
A3 hack_soc_-_mpw-6 7576×1077615152, 0 3.8 MBc284e2d144d35af46308751f08cee9d6c16688475cc83642d6de6f7eb61dc924
A4 riscduino-dcore_d3_ 7576×1077622728, 0 8.2 MB3bcbfc7c810f89e9868798111539476e980ea80a80e281108888fad76bcc070d
A5 riscduino-qcore_q2_ 7576×1077630304, 0 10.0 MBa9ad60dbcff705357a7f07b8ee1ca798cc5263e116ebc7eb3483abdc6434afaf
A6 riscduino-score-s4-2 7576×1077637880, 0 7.6 MB82f11a0e4d923ad74935fd252a2971b67a4da75e5bef4883b7ae810ff056bad4
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 6.6 MBbdb9f3133d4bd575b09d726edee083715bfac7af5605dc2d1521aeb2ad43f49f
B2 ft8_receiver_test 7576×107767576, 10776 3.6 MB513d1dd630383758367cd141a524a9473d5dd16d9bbf85202146faa64a34abcb
B3 azadi_iii_dft 7576×1077615152, 10776 6.3 MB6b6d04d2430dcecfa24b18250b8289a258bd56ba95b44996bae123b00a65f8fe
B4 sramtestvehiclesequel 7576×1077622728, 10776 3.7 MB317f22fedc1596343c32b8ec21debf05d919a0876b40270fe950e0d4e0601440
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 4.0 MB1611af1855f01c43bf371397f848aac0226050d52de7dc0c2ffc21556e0044f4
B6 asicle-ro 7576×1077637880, 10776 5.8 MB3be70117cf8cbd5b0c53ab9a9fab23bc0db4bbb2b9b1f5c21888a17c18e98f12
B7 10b_adc_and_analog_support 7976×1077645456, 10776 3.6 MBc36a11c0191442d1fdc09ebac37b48c35f67d5c3506bd487cf499ba974146c1b
C1 yonga-modbus_controller 7576×107760, 21552 4.1 MB50ab17a7f0ea1137aad46db39d0091cb424c5f8b969a7b836118134f4d5d54e1
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 4.4 MB77ed55a5715d613e40711a5cc88e0a9decbfd295f2b9fab31d044008dcad6b6a
C3 openram_test_design 7576×1077615152, 21552 5.0 MB15ba2e69bd22a48c581a7084799a134d899c425909db6bf239d77387ce7f5cdb
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 4.5 MB99b3b9b100697a581be9f65c4086beed144ff2de70925eb229d99b044f9415ea
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 4.0 MBf71ced466b13a049da297a734855ca807b82a550d3065bbbbea73a411d15b820
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 4.9 MB067236512967084fc0b6c83eb0ddb33a218c390e8ada5240c00076eb3a34da6f
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 3.5 MB66b760d403cc9bfb3a92f8ce22644c61643928d5df9c60051f02f3aebdd3181c
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 3.5 MB9a8990115009c78f3b70f1e7d8abf5e6db129001d79144b6a561543aaae7da75
D3 order_prga_mpw6 7576×1077615152, 32328 9.4 MBbc8b7267295726bff77e8004101ea8c4c5b9950cdce68cb87e063aface06fa3a
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 4.0 MB6ae0e0383877bd5b779f86f480305e778de7e458d1c8073aa9281ac0eaa0875f
D5 large_memory_micro 7576×1077630304, 32328 8.2 MBbc1ec76d950d1149c719ba55233b10291dae183dc5d502c7388e244b82b0ffca
D6 rng_chaos_scroll 7576×1077637880, 32328 4.1 MB68fb3b3c8be5f1619116907c5d01fbe2ce445222623624f19e43c921d3c50f08
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 3.5 MB6d17e07f7abf687500b58d1f0093c986705dac0e82083c81dc540673f2d25237
E1 mixed_signal_circuits_v2 7576×107760, 43104 3.5 MB974968e846cb2e7176483e563cb09110e75a07b0be8d0380b085ee85072c8b32
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 3.5 MB672585df9c280ee5efdacc5ee0a538ab3c0422fd895d69968e3fd0d4f197bd8d
E3 floating_point_halfprecision 7576×1077615152, 43104 4.3 MB0c361fc7ee165bcedac8259f289f81e31929a2db55978d0fa05ef425e6a8ee83
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 4.1 MB027113e003fc1e7eca0c7a81c1c13deca7c13586067a4078e9b2d6352e46d8ba
E5 floating_point_unit_single_precision 7576×1077630304, 43104 4.5 MB740a49cf151dad10ec03829e02226bf71075782b1c3f137575a9ec160ca51fea
E6 experiar_soc 7576×1077637880, 43104 6.8 MB12f59f70461eef9eb48fe68a2587fc12e5944653b5393b3ce10658010627d017
E7 my_caravel_analog_project 7976×1077645456, 43104 3.6 MB222f45c51207b189a18361d14e746f34781094bc102c1485a0dfddf1d11db1d9
F1 efabless_mpw6_riscduino 7576×111760, 53880 9.8 MB765609d86872888e69ac8c4a45b15fc9ad36e4b028177dd2ab27bdf1207e3a62
F2 motius_pong 7576×111767576, 53880 3.8 MBa7ce23ed1464b5d93ce6af2bdd19fbbd9ec033bf04a96f703d71fbd67980896c
F3 soc_now 7576×1117615152, 53880 4.2 MB2a381b73830386608420493a5c2c500597f8fb71557639950968f912ff4c8566
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 9.4 MBd6c97f790b2e2bbd451d28c52bb61086d086a8acb355f3d3b405d3529af01abe
F5 optimised_strong_arm_latch 7576×1117630304, 53880 3.5 MB18a3fb1f036aed35ce07356d2c7e574b218215a600ae9b139c69593c9e421e6b
F6 riscduino_qcore_folk 7576×1117637880, 53880 9.4 MBf1d1e47dccc9366123114a641173b51c8703e22a6c40f9a33568a49227d0643a
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 3.8 MB50aac5e8402f6df3f3d66ecb2f0c1617773819a28690b4eeca0159ecd54e32be

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 FOM on mpw-006

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

Mask layer
FOM — Field Oxide
Process step
4 — Field oxide mask
Drawn layers
65:20, 65:44
Layer on the mask-layer GDS
23:0
Fill layer
23:28
Detail
FOM = diff OR tap (OR grown pnp emitter)
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.