mpw-005 / NSDM N+ Implant

the NSDM shapes of all of mpw-005

40 of 40 dies rendered.

36,320,822 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 (50.1 MB in total, largest 2.6 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-005_NSDM_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_NSDM_reticle.png
the stitched reticle, full resolution
36.1 MB f244ac9f0124a1275771df2b368d347be214cb847aaddad8a91082ebe23e3f6e7591de5d e8d4c40eb8dd7faadb4dbbb0d05643c873d7aa147cae4f0732eaaa32d27430b1
mpw-005_NSDM_reticle_overview.png
the same image scaled to fit 4096 px
1.9 MB a8d2ea2cc1e22d7b9bcb2c677d875a000efc4807ee51f7952860fa87fe06f96e4f25416a 947fa8d24204ce70911eb226f7994d3d987af1c7cda429f366808456e5cb5e72
mpw-005_NSDM_tiles.json
where every tile belongs, and its checksum
13.5 kB d39be418fe6b919873a64453bf4eb31cf115ad4c6fa10b1b4701c035ef3743ed1124ff23 35594c0f1ab33ed33a85a3a8c84af3edc9d4ec613e0d1233361a4c5eb1bdf5c1
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, 0 862.4 kB4dc1c47acd2657eea863dd226000b0305c4a8cf4eeae25301aea694c88923449
A2 mpw5_cache 7576×107767576, 0 954.3 kB87222a30494cd5812a417f71858dbb57b355b08a3609bf056d6e89041912b84d
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 1.5 MB40bd859b83b5a30728d8d0833ce35a3f74249ce0c79e50098700bed86748983a
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 1.1 MBe43ff832c38a4857279d7b6138e72a71674a9e1ed54d08bf9a76fa321b25a9db
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 1.1 MBebe796ac9558979882afcaa97f812a89c82e375dc463ccc3af7ee55180950e05
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 1.3 MB2787e5b13d4da9fac980e629a106703571096afcbb0d6034dc0e9aef1f83933e
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 1.0 MB279d04a9f5cd757fb3f35c9892e5b0e059b597d5be708518561454469059d5c3
B2 microwatt_mpw5 7576×107767576, 10776 2.6 MB092ef726c3555229700d9b95ad41ed46c5f5759bce6323ce7e7b64ed207b3379
B3 armleo_gpio_mpw5 7576×1077615152, 10776 1.3 MBce77bf731d1dc1cbc87fae958c08c5248f8a38efc8db45ace946ed173e9635b9
B4 fabulous_efpga 7576×1077622728, 10776 2.2 MB56746ef007ac8e5790f6ed3e4e67efd5158ed7dc8ab02e11558d58ebc20c2fba
B5 i2c_controller 7576×1077630304, 10776 876.5 kB4028f0364c16e4372f3468467def32cc6592fcd49f1fce1e127a36031c822863
B6 lbist-mbist 7576×1077637880, 10776 1.5 MBc989c3d394f4045fb7fcaf03e35d50d0a569ebe674a1f461a748ebbe4bf81ea8
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 1.9 MBff7277672c992f1c819215d7637c64063a08da381583f87b6c8dbe5a93e37ed4
C1 riscduino-qcore__q0_ 7576×107760, 21552 1.8 MBce852f36737b24521b903aeb878e6e50473afe96edcef471e49210b1862c4f73
C2 high_speed_vco 7576×107767576, 21552 862.2 kB6ae192d861d309e6e67d4712ae314e8fdc6dde92c7112f0191bea8585d189bfa
C3 openfasoc-cryo-gen 7576×1077615152, 21552 917.7 kBd04996add4b072d2959396270ac468769e8ff3965ff77014ce50cb8dd8520da6
C4 microwave_signal_generator 7576×1077622728, 21552 869.9 kB1de7676439895b9441615caf963df5372e0fcacbec62590abcec148c1ea5b97d
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 1.3 MB1ef0e5067d0efb68ed5b7589cb1b3acb27d2c6a5841cbf153efbd6af686dea74
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 867.9 kB7cde49f9a31e90ac554f1ba167ea286e01e6e0d3bf1a1f5e7fa2808ff745f10f
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 849.0 kB7c3920c8b384cfbaeb3c2d5ca6d5d3ef09d1ab0be58f9c764300ca0009fda862
D2 azadi_iii 7576×107767576, 32328 1.8 MB5a5d256a83a2906bfb638cf16ec786d221df93a0f8f6cf0bfbd727bfe957c9df
D3 tia_for_physic_experiments 7576×1077615152, 32328 853.8 kBc353151bcc09b69460f0bc453b9fab1f06bbd485aa318b2eb9ef500276948b70
D4 qf105 7576×1077622728, 32328 1.9 MB1df968e8ddc3ad64408995ba60c250bf67ff7aa02f96e667ce09a6efa3962f33
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 2.2 MBad6669cf96753b5982a1168a29151b91120f64430749791af51cdf04b6058a0d
D6 junga_soc_mpw5 7576×1077637880, 32328 1.2 MB7fea68c09dfe48931c7523fe71b70b3bc0b1a1467aef8011370813b690a4d529
D7 nand_flash_mpw-5 7976×1077645456, 32328 833.5 kB17e21205ce599fb72ca84fff03569f004b16f779cf372fc679607b5b29241e99
E1 kasirga-c0-mpw-5 7576×107760, 43104 1.3 MB6aa4959806f26b8443b307b8e7995d95618c8f341146904c6bfecab6e272cb25
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 1.5 MBb222291bcf5abcbfcc0b7199b4eef979d0f0885653cf06216c2d2b5cc153da8c
E3 wirelessenergyharvesting 7576×1077615152, 43104 840.9 kB799e843a1374469c344ac98ee03451a391107c5081ccd7db7fa8d716f6b7d2a0
E4 caravel_raster_engine 7576×1077622728, 43104 1.7 MB34f426d58774f0888760d11859b4f7464baf6d7fd411235f1381e512fe254714
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 867.0 kBb6b8d8f9837716445a6827a359b2361c84809aa7b3f5539619797df451c888b7
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 976.5 kBc07873d93a11d883cf5fac29d1b6b5c260f46fe4fa849f4fe8ac5573d9d83ba8
E7 alu 7976×1077645456, 43104 941.6 kB988202e7a21008af2994f779a30c18c5a05a9b832f5a054fd3dd4871b371a226
F1 4ft4 7576×111760, 53880 1.0 MB84285f773a0e9aa675be7010eacc8a48665372c15f3df0244c07f09feb8efcb4
F2 rng_chaos 7576×111767576, 53880 872.3 kB72ecef8226d60ae617d9202b7058e3de49f53b16081e8c88d3b52f11196c179d
F3 uetrv-ecore 7576×1117615152, 53880 1.4 MB773b01fec3d83964a8ef0329242c7d00b5fd5898619db7c2581801ff30992ed4
F4 systolic_array 7576×1117622728, 53880 971.6 kBc225c125a99b2ecbcedb41de6bf0ea5f6d1951e5ffc3f7d3068aeb4e8c7ff3ed
F5 reram_test 7576×1117630304, 53880 870.8 kBcd7dfe3f137f1ea22380962c47d81022b4752cc9d0b75578b86866020d85590b
F6 secure_memory 7576×1117637880, 53880 1.1 MB584e8dbc45e8000198e9ce9f7e4965f0f7915c98a295a1fb9730ba8dacc0f15d
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 972.0 kB122f8bacf3704acee6df18ae67de8f8f41e3765b84641ac28b0ac1d3249c3f1f

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 NSDM on mpw-005

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

Mask layer
NSDM — N+ Implant
Process step
85 — N+ source drain implant mask
Drawn layer
93:44
Layer on the mask-layer GDS
30:0
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.