mpw-006 / NWM N-Well*

the NWM shapes of all of mpw-006

40 of 40 dies rendered.

31,680,319 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 (25.8 MB in total, largest 1.3 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_NWM_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_NWM_reticle.png
the stitched reticle, full resolution
21.5 MB da14159cc80ca3e607950917a93f7ffb996a011d495588439f1c1ab642a50c1fcfa3dfd9 2d26eb6ba7bd487f034bf4178db0f53d83d4104f27cc9567df297858360de51d
mpw-006_NWM_reticle_overview.png
the same image scaled to fit 4096 px
1.9 MB 1d37dfcdea4ca7c207a99646d9484ae3275a601b4b3038ffaa5a206e254547192b3f5314 74ada4fda49d4693c7b882b2d09c53db0556af34bc60e146a6e7f3db61503129
mpw-006_NWM_tiles.json
where every tile belongs, and its checksum
13.6 kB f715fe8d57f3e35a98b5d6c2b10eccebd96ed3562d739995f3b203f69334e425c8d5ca7a 6a554a5c5e7f033d8e2169dd5ea843c499e1238833c328a79937865e5fcb1901
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, 0 462.1 kB1f20c67bdc0e1688fff5381b4cf9e06a6f9f83ba71e3d8fca46e88b5cb37e546
A2 microwatt_mpw6 7576×107767576, 0 1.0 MBe2a89557521ad98d12b06f2a8b25cb465da53e0ce80e5104a31edb7f1a0e4834
A3 hack_soc_-_mpw-6 7576×1077615152, 0 493.7 kB862d382aae497b3743af26b99a7bbc6a019980826215b57c26c1e5ae57e21f0b
A4 riscduino-dcore_d3_ 7576×1077622728, 0 979.4 kBfd44db0ddc6d5b832134b1e89d99308211bbaec61260e5997242d5096e2da0b3
A5 riscduino-qcore_q2_ 7576×1077630304, 0 824.9 kBb6426d443820e0e0a71cff4abcec9f82210995ca9a9b0935063746313e58fded
A6 riscduino-score-s4-2 7576×1077637880, 0 767.9 kB4bccd0ae545519e6af4ec776387e4eb144b9cbd3695a884f6fadaa4cae98954d
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 791.6 kBcd8f68b20a41b19b09512210091eb5e5bab03578afe39859782b0535e4764046
B2 ft8_receiver_test 7576×107767576, 10776 429.2 kB27378024854fdaffc4dd8af5a82936e9a0ff008affec0d326fcf3aef8bb739a3
B3 azadi_iii_dft 7576×1077615152, 10776 803.2 kBde93dabf38ea359c7580c94d6f2ab2115143922374315bd2719186199d0861d9
B4 sramtestvehiclesequel 7576×1077622728, 10776 434.6 kBf62c8f4bea18ba9f2b6efdabed56848823ac5a7c7959bb34cbdd5141bf3af9f7
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 481.0 kB4d599aae67bfeef80ec1ca22a225229cfbe5952e5a42b354d8d44e915513a8de
B6 asicle-ro 7576×1077637880, 10776 758.1 kB5224a3d96ea1057252bf847af411f92e01b9c553d2e38ffae225fdb357f11c62
B7 10b_adc_and_analog_support 7976×1077645456, 10776 455.4 kB015946ec23b6b378ec7ce48e6a5689f02c37c14c05948554e90ecc6d4a6cf0a1
C1 yonga-modbus_controller 7576×107760, 21552 528.1 kB85aee529b2ec19a2876526611dab143d8776c4d6f054ee99d71cf0da57d79acd
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 509.4 kB3f8c1908418ee0c1632d54b62c754d209090aaf47d08ebcd66633d93b490271f
C3 openram_test_design 7576×1077615152, 21552 543.6 kBeecad35b586fafbfc9aa09c2311aeb5b4d5968165a5e9f022b7cdace70c3b0d5
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 513.8 kBc49432a8294e60596809fd89c4acbad35a210d639c98c21cd645025da27f36f4
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 483.4 kBc541c10eb2dc45a9373961fb666e2ae41ae153a78d99d4a49d2f48c91b14b2c9
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 579.6 kB12ffa451b7d6493b98279e163696a63d23b25bcfc2746da1e866f686fe8743ac
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 453.6 kBda492fd51a86916af99bbb0fb28a37486b23da3cb1d2172400c7847ad9d8bae2
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 456.4 kB45818eac3d18d43b344e3092fcc4fd0e3268dc6fb4b73ab66235719f5d9b5297
D3 order_prga_mpw6 7576×1077615152, 32328 1.3 MB32aa79273e306a30e21d588d8829f6e166aa732a555fda0425d3cdc5898a50e4
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 517.8 kBeb07990f2bbabf3582b940c661a71ded330ae2addc75d4797da054e28bfba82e
D5 large_memory_micro 7576×1077630304, 32328 927.0 kB2becd8c2fc612619754d50f0102f966ca6a051138651b9ee59d8680f76d90fdb
D6 rng_chaos_scroll 7576×1077637880, 32328 543.9 kB6e9d0cf3702c662e6d99544c0d510008eefb713ead7d696c9fa7d33d306b1fd7
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 486.2 kBe4d4467f695fec483b03b79d1453e71b372cb32fabb1bbdf3e7c7a872114c7d1
E1 mixed_signal_circuits_v2 7576×107760, 43104 466.5 kBaa226c95c562d765b0096d146dae182bbee01fda5a76adcee101748026c0d0c2
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 469.5 kBd537c6777b7b2228eafff5378048522ca5a22033c83bc8aab11c8b462b9bc059
E3 floating_point_halfprecision 7576×1077615152, 43104 536.3 kB314e294b86dfe3e5bf19b541c4f002dae0898ee41cc81d96a4ad7beab14bd013
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 576.0 kB5d8abeb69751ce0dc5f4ad45ce1c674b0640afd8c8245b0b78a271388859bfee
E5 floating_point_unit_single_precision 7576×1077630304, 43104 541.0 kB2f31aa034b686dcbb4c7bb71486ab3ec69585078a44b3e0def8f65fa78633ced
E6 experiar_soc 7576×1077637880, 43104 782.5 kB00069273ae70d876b836174366347af5b16375046c57e308d4227eae45fd89b5
E7 my_caravel_analog_project 7976×1077645456, 43104 441.8 kB2a362926f52580406112042b3c5ea08966e9461004a59527cabf6df521730a26
F1 efabless_mpw6_riscduino 7576×111760, 53880 1.1 MB8709ed29f347d56eb21db163910e6e358ed4a400c162ceb04b563ba1a54b5df4
F2 motius_pong 7576×111767576, 53880 514.6 kB939de99699d2dfa0ced9e2c9ec6382a42d0a4719704dd0fca84a308f158a76f0
F3 soc_now 7576×1117615152, 53880 522.2 kB35413569fa1ca363cfd056df73fb4a04172c3dc07e692847b21183820a0fdf99
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 1.3 MB9f95fad68a2d56b2069b249caf0b3436183c5eed2fa497726a466c7642cb4fc4
F5 optimised_strong_arm_latch 7576×1117630304, 53880 435.4 kB3e48705dee27ff9ceadd009817b0819dc089f0be4ac8c874741f8555c2da2d1d
F6 riscduino_qcore_folk 7576×1117637880, 53880 954.2 kBbfbaa4622fac134ec7918fefd44944ef1ca08c59eeee774522c912ab906e9fd9
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 524.5 kB8b14042e6bb1b548de55dd5391b4a630ec7be25b94a9b360bb01340910c6cf26

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 NWM on mpw-006

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

Mask layer
NWM — N-Well*
Process step
17 — N-well mask
Drawn layer
64:20
Layer on the mask-layer GDS
21:0
Detail
NWM = nwell sized (cnwm.3a outside hvi / 3b inside), with DEPMOS/pwell-resistor exemptions
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.