mpw-004 / NTM N-tip Implant

the NTM shapes of all of mpw-004

40 of 40 dies rendered.

118,511 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 (7.5 MB in total, largest 293.5 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-004_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-004_NTM_reticle.png
the stitched reticle, full resolution
5.4 MB 28b97310144498d8a7cfeb44d3b142171963b9b63a8548a6805173ffa64f6e7ec1d6c112 289af98b1ea6da15da9a31a3b596aac6285a2779d8aa7daee9963d9379835a72
mpw-004_NTM_reticle_overview.png
the same image scaled to fit 4096 px
556.6 kB 27599cd00dbdfc41da7926ca9c54cff3656d1fae884c62ca9d20d424da1a04c8ee69432e 6a48514b1e178b976707791839c9bc5ffea312bcac2dafec7a5ce91a0148ec1f
mpw-004_NTM_tiles.json
where every tile belongs, and its checksum
13.3 kB 82a839121498bca3f507f385e79153c446343f9c2442c048ab6952cfa563281774accdb6 059d5e93b3a2820e3fce2d2e11df64d58c98cc65e71e5d74f35f32c09ed7da18
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 zero_to_asic_course_group_submission_mpw4 7576×107760, 0 185.5 kB5b0cd72f82f1af83afb6cfa2a78ab83eb7f103eaa39a25601fdd859655d1a0a6
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 177.5 kBe2d1f7cf35ed79d2d43ad646fa1033b13990d82ae4dc745f0f7e8d1a485d98c0
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 161.0 kB5175c4b3f568911351a03b0217e680646d1a2e53144d65561cb89434f6ccc8fa
A4 pifive-soc 7576×1077622728, 0 171.0 kB8be89301a958b9e84214ebfc01d7fec25e92c2ebc10f7d9182d70b74e220b9dc
A5 ram_generator 7576×1077630304, 0 178.6 kB85d3dc631e24767daa80099c95142e7df6d0e45ac2ed2ee1a1d65056ea758191
A6 space_controller 7576×1077637880, 0 169.2 kBda530094f2ad7b88635e722c7c0877ec25aa094370ef8f4bf4c5aee2fee3c5b8
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 173.8 kB272c4fd80919df1c3088160c156a283981937e4a68b3f370ca7984a1e69b5050
B2 4t1r_testchip 7576×107767576, 10776 161.0 kBccbae48367266407eacf81199837b96fa9e25ca6fccd5e04e70a243bfc5e5550
B3 yonga-turbo_encoder 7576×1077615152, 10776 170.0 kB7bdbf9595b45855eef0ccd8233ac2e581547ee165b36d344cbca0405b876a814
B4 icesoc 7576×1077622728, 10776 293.5 kB08f52d1b363bfcbc279acdfe98477c2a54b0fd38ce46476bacd42d992e426d5a
B5 key_value_store 7576×1077630304, 10776 167.0 kB882bf3afcd44c9acdf7ed5a9a1a2fd19101a4c40015dccd39ba545368426e964
B6 subservient-mpw4 7576×1077637880, 10776 170.3 kB38c858029620d598d985f04dbc8e942058efe2db4f091c7863ee1061c3b33bfe
B7 logic_bist 7976×1077645456, 10776 224.3 kB212da79f7b3bf18156f6b1708a9e4ddebca732b569fcb67b094c5b48ea6da5d2
C1 riscduino-r1 7576×107760, 21552 195.8 kB7499d7afa35c20bed729d265c6102f67c8d37fbab3f8f77baa8090f08e4090f3
C2 template 7576×107767576, 21552 168.4 kB31e1cfbd965668a4b3935001a04fa6bbc291244795e7652a3edf894716fdf982
C3 vexriscv_soc 7576×1077615152, 21552 173.0 kBc2109f88f4c77ab75357ea7ef7619aed0f05e01ca2dc94e1a44fe72659881440
C4 ring_oscillator 7576×1077622728, 21552 160.6 kBb34de74f32d28f8c117a7419bd90c3a84929480e2b97cb289bcf795b446f4ffb
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 160.7 kB0d36cad3376a436aa7c65d58a9988a1604379d366d7a2bbfa6e9cdd832bbdd35
C7 approximate_multiplier 7976×1077645456, 21552 174.4 kB13f12241f2a2d9fff24e23e81b502fbcdbf083c8f21c5ef02749dd4429b0414f
D1 icd_fast_nu_mpw4 7576×107760, 32328 161.0 kB44984e6bb0e0bf55cb475f759aac51c26dcabc54da314dd7d750050588b59cce
D2 rram_testchip 7576×107767576, 32328 201.3 kBe8f2ab6d8d9310c271a76ec0c0c3228b2e2095c23746b8f3a20ae287fa35cd8d
D3 rest 7576×1077615152, 32328 211.4 kB95faa350ad0c1225fe4120be3829eea87a02f2653df7b50683ae2550ac14de03
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 166.7 kBb7bbcb1a4102de0f4bbb88646c3074535ed08d4974e166b20658f51972aa684d
D5 sky130_radtol_test_chip 7576×1077630304, 32328 199.8 kB2206de73cf0f446181e04ccb0d0a2499e95a778a1361fb8af9109d3a64c56c22
D6 two_stage_cmos_opamp 7576×1077637880, 32328 160.5 kB46b62a502aba095b299a9bb03f1477d00477088a7225007481c61f96e8d337a4
D7 ks-guitar 7976×1077645456, 32328 177.9 kB23a547a3469dc908f689e2f0246ffbbba669be40f9c7f313e6cc6f923e85b4bf
E1 ks-guitar-2s 7576×107760, 43104 177.5 kB1d62e886e1a201c4c39cfb8c1e7e6983bc5684a7be9286a0da3697f92214a9b7
E2 yifive_a2 7576×107767576, 43104 197.2 kBabb54ce7f38af1f96881f1e4a2db31841d5fa7d47d391ce06540db9682d78e74
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 169.0 kB7ae5b11fbfb8e8ab8fb837571867ad53fbaacbded345c73a04be63124639342b
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 161.6 kBf242b151471f9e495127406e78f4c97fdd5308b828b191f21188807d6e096b07
E5 junga_soc_mpw4 7576×1077630304, 43104 173.0 kBc2109f88f4c77ab75357ea7ef7619aed0f05e01ca2dc94e1a44fe72659881440
E6 ibtida-ii 7576×1077637880, 43104 175.6 kBac5b4aa395e313f3241e39582fed640eb59c08a113f21c3dea6426c5ff28b9ba
E7 azadi_ii 7976×1077645456, 43104 219.8 kBdc607e26c03de5383f0bfcadaa40a34566fc549ce621296242999e38273f1073
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 282.3 kBc7af01d9a2e22e73843b6b972656e0a2f302b2eb48b8eebebc12b51f53170b45
F2 current_starved_vco 7576×111767576, 53880 164.4 kBadb8b52f4ba42ff9dc4445a23e59d77793b6be4e64ae310890f82885c68bf3d7
F3 updown_counter__test_ 7576×1117615152, 53880 172.3 kB6b4d97139b6db9bd92c1d8c1c2b2229174fbd134a344ce98e589a7083002a381
F4 skullfet 7576×1117622728, 53880 164.4 kBa7059636e14df2ea432b76c31a9df57e1c6890930bdca2bdcb6741d479252540
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 164.4 kB3d960e9e1ed79aad0de0ec051943f72f393b3564de70a0a89e971a4862612f08
F6 kasirga_k0 7576×1117637880, 53880 183.2 kB0a8653fe433228505329aacb86ef250b0a0480f7bdfaac9eac12bef53896be3c
F7 iotestvehicle 7976×1117645456, 53880 170.1 kB8cc767db1ee27da565cb49b69add4a40b8cac6284570790438779404746ce79e

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-004

Resolved: reticle 5CS8010AC, run mpw-004, 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-004 — SKY130 MPW-4 (original)

Foundry product
EF MPW#4 (+ 'With ReRAM' split lot)
Reticle set
5CS8010AC
Run date
2021-12-31
Submissions closed
2021-12-31
Projects
52
Fab lots
4216266
4216266
4216266
Identification
confirmed — Lot records: EF MPW#4, lot 4216266 = 'SKY130 MPW 4'; the set is absent from the 2026-08-25 return shipment (destroyed 2025-06) — see 5CS8018AC
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-4 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-004/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.