mpw-005 / NTM N-tip Implant

the NTM shapes of all of mpw-005

40 of 40 dies rendered.

110,972 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 (7.4 MB in total, largest 274.3 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-005_NTM_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-005_NTM_reticle.png
the stitched reticle, full resolution
5.3 MB c10fe833ed14249690482ff7ac56e6115d0adedd51bc70f1f5dc2871e763dc8602a75db2 eae7c299d7579682e482539f00d829957cc7e8bf68207ad12c7354597fb7a9aa
mpw-005_NTM_reticle_overview.png
the same image scaled to fit 4096 px
540.0 kB 850f7b23eb680c7128b2eb793088758e316d76638a830aa8141a37d8ad89ce178a5a32a5 c95f2fc15199f93368cb8b9786764e78184b70bfe5addd05a4a9f546d794d9f9
mpw-005_NTM_tiles.json
where every tile belongs, and its checksum
13.5 kB aa0316c55d583c3c25e2f05e0feaffc6c2437b750ccc0977603f7316d339919a50589d56 77b31e300db4031dbe6865c82f74446586ec7dba9c8e2f646983d70f4d090ea9
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 pll-based_capacitance-to-digital_converter_mpw4 7576×107760, 0 160.6 kB9f2f9d6a3c34dffbea99d097aa6e3d24ea978e08dd663d1241e6572d74b7394e
A2 mpw5_cache 7576×107767576, 0 168.4 kB31e1cfbd965668a4b3935001a04fa6bbc291244795e7652a3edf894716fdf982
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 188.2 kBc88384953faf51d367e92ad82dfbf4d2b9a64b6c2b83923fe10f58ea809bd237
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 177.5 kBe2d1f7cf35ed79d2d43ad646fa1033b13990d82ae4dc745f0f7e8d1a485d98c0
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 180.3 kBc8b7813fb55ecc385d724e327243ba5a019d8c9be03290588eb8ef3cee362f28
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 183.4 kB312d3202f4b944e2577c3c48d5ce7b03748632f9795f8c72e4bd5b64f5b16467
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 169.8 kB2d63463ec7f52857fc65c3bf42e92e6649050ba667017cb77fc7b72379c454ad
B2 microwatt_mpw5 7576×107767576, 10776 205.4 kB49560def72215d59393bd0bb5407770f8dacaa7deca90bb2766fe8b8867944db
B3 armleo_gpio_mpw5 7576×1077615152, 10776 191.8 kB1ce053ab61e614edb0422157b49457e61ef9e72789a1bae65aa4084ab0650834
B4 fabulous_efpga 7576×1077622728, 10776 274.3 kB45d13f474c65010553107c3e26ee037ca0ced9d23bd4710e4429505e248bc934
B5 i2c_controller 7576×1077630304, 10776 168.4 kB31e1cfbd965668a4b3935001a04fa6bbc291244795e7652a3edf894716fdf982
B6 lbist-mbist 7576×1077637880, 10776 202.0 kB7b49afe8e734900de4557c0325df070a0980d93558f43fb273a686c62e5cf9e7
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 199.3 kB020777b109970a9346561677d9cedc1ab89d7b4cc4857192e816f57275afb660
C1 riscduino-qcore__q0_ 7576×107760, 21552 194.8 kBd5455bb96d47cc348deb89534468d103e2ff87567cf8c1e338e29fb01924e78c
C2 high_speed_vco 7576×107767576, 21552 160.5 kB2d8af932008b40131802f42de09d642a4dad2964a2b1ddb4601526fdc82796ab
C3 openfasoc-cryo-gen 7576×1077615152, 21552 172.6 kB271030342d2a5ddc7c5b40c16ac7b6d4232f29777bd0115d95fe99be63138fee
C4 microwave_signal_generator 7576×1077622728, 21552 164.0 kB55782f8adc965f997e263982f8c2c9d511ebb072c8f3587b412e47d81b934201
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 183.5 kBa7b454a152cf2c883004b9dbab8f727aca3a8d0e737ddadfec94d22a21ff868b
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 164.7 kBe0ffcba2ab09f45a1e6158c45ef51b31a9040731c8f79049f8f2605aec1269ac
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 160.9 kBa178af6c5a1b0130c108cf471a36ff404d7acdc15890f3b45a8e23979303764e
D2 azadi_iii 7576×107767576, 32328 235.5 kB55be297a09355ddd5d45107ea69d972aadfb0a03640dd13e43d16bdd2322b512
D3 tia_for_physic_experiments 7576×1077615152, 32328 162.3 kBcf5885cd9d9cd122e6ec59f21da0273888607c794a1a1a0ec3c5a461724d39a7
D4 qf105 7576×1077622728, 32328 202.2 kB8e8ebc33120dd28be355629755005bc2a80bc1149347cd33d4c5d9cf7e355399
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 169.2 kBba0f664476c73d9c5a6e650dbed2e3f0593e7c1e49c526bc26fb57d7e223b7aa
D6 junga_soc_mpw5 7576×1077637880, 32328 174.0 kB642d00c70b74fe2fe019c38a9f72280c0d7de2e35aed29a820fbe57a6b173c0a
D7 nand_flash_mpw-5 7976×1077645456, 32328 170.2 kBc6a3101ab8d26781a7826dbcb0df926e6d2f7cfa0536d572e144184eafb2fca8
E1 kasirga-c0-mpw-5 7576×107760, 43104 178.5 kBbc799fab7d86323fbcd9d3cafeef44168179a77de1b8e092e888fd451ae1b17b
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 175.0 kBdc9dcc6f05c9f0dbde44c2284fb386bd62fb1ba4141c00bd807e46c1beedcd2a
E3 wirelessenergyharvesting 7576×1077615152, 43104 160.6 kB06b14a433536d9d14234caba11839596cbe44591d3321699318d2823384a7d39
E4 caravel_raster_engine 7576×1077622728, 43104 171.6 kB30c810373f2422c143f8809b9dfc9f7b55d09ebc36d9015beb3316470a5ab518
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 164.1 kB4e5bc1f9dfdd8d90fb28ec65071d216978c53660bbe211f9be56c9ce57a10e25
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 171.2 kB5605712c20e07e9b25dc66a7621fbab42c3ea9eb9beea2bf4f78228031b92c72
E7 alu 7976×1077645456, 43104 172.6 kBb4a33e8d737f8488b2e156217803f2e96ff4657f5403f6f9621050c23fcf2ead
F1 4ft4 7576×111760, 53880 173.3 kB79f4db016ec2f44e787cecf5f9f30903f2418416e215fb77c3056e5ad391656c
F2 rng_chaos 7576×111767576, 53880 170.7 kB661fabfd032577b778fa7f649146ed258f369b7a5c0a8afae2639d6c8848a6ad
F3 uetrv-ecore 7576×1117615152, 53880 186.1 kBe63a36b725684884bbbfb013e92e3b268b9f0550d684aa999490d0a8b85e6ad1
F4 systolic_array 7576×1117622728, 53880 173.4 kBbec0dcf4b93e59f79aa3d8a6a819f6abf11b6c35009f2d31a8ad61db510b992e
F5 reram_test 7576×1117630304, 53880 164.6 kB1e07d119a2f1fbbe3babb56159128754ff09261d4a9a5e43c1f4c22916b9c9b2
F6 secure_memory 7576×1117637880, 53880 177.3 kBc7da0b235fe927fc0ce66bfba69a6afe853111e6557a2e44236c034e8cbf95d6
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 176.6 kB68e4d08d07fafb41be3c349f5c8034380c7e7d78b93a95e3b8f0ce8e372f9fe3

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 NTM on mpw-005

Resolved: reticle 5CS8011AC, run mpw-005, mask NTM

Mask layer
NTM — N-tip Implant
Process step
64 — NTM mask(tip fomation)
Drawn layers
64:20, 75:20, 11:44
Derived from drawn layers as
64:20 OR 11:44 OR (75:20 NOT 81:2)
Layer on the mask-layer GDS
27:0
Detail
created over nwell, ldntm and hvi (outside areaid.ce; rpm too in some flows) (cntm 26:20 is the fab's precomputed layer, not drawn)
Used in SKY130
yes

mpw-005 — SKY130 MPW-5

Foundry product
EF MPW#5 (+ 'With ReRAM' split lot)
Reticle set
5CS8011AC
Run date
2022-03-21
Submissions closed
2022-03-21
Projects
74
Fab lot
4229389
Identification
confirmed — Lot records: EF MPW#5, lot 4229389 = 'SKY130 MPW 5'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-5 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-005/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.