mpw-005 / HVTPM High Vt PCh*

the HVTPM shapes of all of mpw-005

40 of 40 dies rendered.

104,428 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 (6.4 MB in total, largest 250.1 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_HVTPM_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_HVTPM_reticle.png
the stitched reticle, full resolution
4.9 MB 5c926660e57a2f2d8b96c3a873ce54ab9019834ec7d1b63e87f64f559c6af99a0928612f 6e5a02d10ab871e02eea14b2fbba85d8f1fe4e0fd5487b4e3f043eef16fee14a
mpw-005_HVTPM_reticle_overview.png
the same image scaled to fit 4096 px
413.1 kB 048b483d93b4ecac743eb7f5b9d6f7ceed86603b49e3bed4a45b93a6c8f0b0f3470470af 10f5d7f3ff7e45a871e410c37daf95d8ee1db66a13fe21b6d29d04e2bcc50443
mpw-005_HVTPM_tiles.json
where every tile belongs, and its checksum
13.6 kB 90be0221b227ef032e452472e222bbd4ceeb0340c57ff8f8caeb198b0d53e2d6eb8d4b2e e170f5618e82b4685978d2abe701b952b9a3508bd9d69762cd880d709dd5f8a4
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, 0 139.5 kB288092c3bd16e0c6b8bb38aec7d146716a9ca40539fd4105f863f0fbdab8ee6f
A2 mpw5_cache 7576×107767576, 0 144.0 kBad3b8f85edfd4b71874f5fb528e8b7542537ad424eebc643195136b1e26f5da4
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 163.6 kB00752604f9c9b54f5ab0f76dee2ede13e552185932eff690b41a1a42d5f6c93c
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 153.0 kB8e4f9a0d938f06df32aa777da8a77971ced9e2920538b8d21fda7c36225e9b77
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 155.8 kB6862d41915901ad2af182f45c406c272a85cbaa9e79637eb83ca936d66917a71
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 158.8 kB049643f288f8e8022d798a2430bfc6b4be1e9505caa9630c209a54b1ed5a2fa4
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 145.3 kB87460290a27ba49c4aac88129c6f16d306f4f8588cee47ae25ebdc9d6edef855
B2 microwatt_mpw5 7576×107767576, 10776 180.7 kB93b5d67eac6303468b9ba8063c1862e23949b8c6de36b45c386c4f7e14f3c4f5
B3 armleo_gpio_mpw5 7576×1077615152, 10776 153.7 kBa34192af3c25f3799c06a13e8ac0d33d323a53049ec0e1484f7175d2805bd567
B4 fabulous_efpga 7576×1077622728, 10776 250.1 kB0735807d6dbc423f8e811ddb76918f5aad77da19c642f3967ad9f3858c50fcbb
B5 i2c_controller 7576×1077630304, 10776 144.0 kBad3b8f85edfd4b71874f5fb528e8b7542537ad424eebc643195136b1e26f5da4
B6 lbist-mbist 7576×1077637880, 10776 178.2 kBaa8dff563fdf5308d2bcaaf84f3d25cea99429be501cd4ff9f7bf1a3d43c6c5e
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 175.1 kBafc87153f3e66e31fa7064b9d23a52320b52b9d5c09e569ae7955817678e707b
C1 riscduino-qcore__q0_ 7576×107760, 21552 170.5 kB72fe1b036ec342c7685250f859e657346d378246dda744e55e81a6c36fcd5edf
C2 high_speed_vco 7576×107767576, 21552 139.4 kB63e2a7afe6c249abc4df8898aac7daf2b4759e679bf5ecd159c7ba725f6c409a
C3 openfasoc-cryo-gen 7576×1077615152, 21552 147.3 kB2f7b18b13635b384e449cec2d13624a1afd0af6fb6ed217359a86709165af309
C4 microwave_signal_generator 7576×1077622728, 21552 142.9 kB567c32618821d6c478199386aedce34e16bc9994f324aa185c7f40fe6eb3f5ba
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 149.9 kBdc692ea7f7863c795be204dadf275583a9b025f6dfcd425fa3898a37a671f382
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 143.6 kB4ef8dfd53fb2766a0cd2ee5382699d2029e4e22e473950cb46a19e55e94df5c8
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 139.7 kB1e83421ef34e0a777f94aa5408a21d77ff0114530011bee5dc4b19b03625409d
D2 azadi_iii 7576×107767576, 32328 211.2 kB6283ca336aa1b1853f6b90e8508eb4c17f146ac0798e963b488594c9cfb10815
D3 tia_for_physic_experiments 7576×1077615152, 32328 140.9 kB9809366a15a053ed749f513fe7a9dc27d02751be30800c85d6f4c484c46b2ab0
D4 qf105 7576×1077622728, 32328 177.3 kBd5723ab673efc25fce6a744abca944d7fda6e1fd00ce8a849b72bfe6b943ce61
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 144.7 kB9e46c908111059d837320e5825165ae07d00989c1eb76e94816dc2ae69d2669c
D6 junga_soc_mpw5 7576×1077637880, 32328 149.6 kB06fb525f20afa4b824ee7312ac1ae9728a87b64d53d7141cf3cf402808a12567
D7 nand_flash_mpw-5 7976×1077645456, 32328 145.9 kB340322fb9d5e6be8fd11c57207f6bcd495980a861d52a55b439b5cf2435e0792
E1 kasirga-c0-mpw-5 7576×107760, 43104 154.2 kB466da3a2458913bdabb7bb862830fff70e9c541a779aa16be1a87bfbe8fb02a1
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 150.0 kB50a3a857ca1b65f76a246f351fe5d1e6b8c82f14a579af9bcbc3176ed5fb655d
E3 wirelessenergyharvesting 7576×1077615152, 43104 139.4 kBd8edf9084ba720a3cd97e55a9cb4f46059534cc6126ac4fcda2f10f4240e32ec
E4 caravel_raster_engine 7576×1077622728, 43104 147.0 kB4981ca30322e6d566ca4a0766dda6064681041f34038f54c4b2880593270dae0
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 144.3 kB52f9026bf77c5c2420ad2e91a739930af3f1665f4a8d802ba909db04671125bf
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 146.8 kBe40f075f6d00f0c9198bf4cc6524f052522aec4e711c6668fb46e18b346f1d6d
E7 alu 7976×1077645456, 43104 148.3 kB153bbcda06161e1692817d2d3147104366d923343d4a0fe46a9f9c6a495344f0
F1 4ft4 7576×111760, 53880 148.7 kB81c8f42fe341561ed7ae3c6e6da9bbb2cc88480bf3db58ad7e54c2f4a5b3353a
F2 rng_chaos 7576×111767576, 53880 146.2 kBb2c74ffe5a9bfb409977bae6fa6f5397d4336127a0b857d27c6f29461b8aa8e6
F3 uetrv-ecore 7576×1117615152, 53880 161.7 kB30b64d9e07d499c79797cea39549b391e0ea971a814d77a964b8d7489fd16893
F4 systolic_array 7576×1117622728, 53880 148.8 kB95f6418f8a309280dd8b4191cf870dd53749a33ed4674e3ddbf96b4bf1691653
F5 reram_test 7576×1117630304, 53880 143.2 kB837bc573b16475160557b381272fac3f9d947a9263696290e34f10f71215af55
F6 secure_memory 7576×1117637880, 53880 152.9 kB7032a668f8c9190a9c8eda682d0a6df29c4d57cb460aa20e129b846a7d53d431
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 152.3 kB4fdd0650772bf623b3d7462137aad88ad36dabd664a4b29f18a3f098a4b11cae

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 HVTPM on mpw-005

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

Mask layer
HVTPM — High Vt PCh*
Process step
22 — High V P-channel implant mask
Drawn layer
64:20
Derived from drawn layers as
(64:20 NOT 75:20) NOT 125:44
Layer on the mask-layer GDS
97:0
Detail
created over (LV nwell = nwell NOT hvi) NOT lvtn, plus hvtp only where nwell overlaps a varactor; the fab algorithm says do NOT OR hvtp in. Rendered as nwell = a superset
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.