mpw-005 / VIM3 Via3-PLM

the VIM3 shapes of all of mpw-005

40 of 40 dies rendered.

34,408,584 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 (15.5 MB in total, largest 984.9 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_VIM3_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_VIM3_reticle.png
the stitched reticle, full resolution
11.3 MB df64189948652b05a0b71a595bf65fadeb2c0e6a670a446c6fbbbeab194285f69394817a 6ac3913167420f3b62176ce632a233bd03334c040b288c1477130339c329f0cd
mpw-005_VIM3_reticle_overview.png
the same image scaled to fit 4096 px
484.6 kB 9e8514f06dc1a0e18f2a7bd12069422959e4891f40e3242b5d0e82d27314da559e2263f9 70b761a9006d2bb66a4c507d8957a962714d7afe9032e30fdbc24f954bd754f0
mpw-005_VIM3_tiles.json
where every tile belongs, and its checksum
13.5 kB 988dac44049528a6b82753d954bcad09e02b5d0dbaa76969839d648463ef8230aaa9cc3b 6d369e7ab5772ace413e403b55c54cdf9af7b38dc67581e761e64498fa7ab871
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, 0 292.6 kB71546e566edfcfda7f31dd41eec76a0c0f18306a4bf946151a0aa35af83b1c11
A2 mpw5_cache 7576×107767576, 0 327.8 kB909ad5b8047c3e32586df5d9039c300a2c32ae47646a5edbb4bd93de59af498a
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 398.3 kBe7623b8a3544b29ee2f8e6a86d32349e0d94094be9cb145fc97125a3aa9cfc4f
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 362.9 kB3726c1880f2b165aec1153db9ef1d87af63e1e40b051a5f3b6232e90457bbc16
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 355.3 kB769c04fd7ce0c9c40856ab4b96e66eb51ba918bbbf1edf31b3344f7214119f30
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 402.7 kB011efc766541818291a3f3c41c3a1fcc0ab7790104f492f690d2400f70397fe4
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 328.6 kB203e6a1fbbb9e9c52c549a11fda7d38558d96c7b7a12575e601329f4cf72ae3d
B2 microwatt_mpw5 7576×107767576, 10776 564.1 kB001af7a8f410a1a4ed8c4cf5a9d442718c549b4f212bf095999370547b233425
B3 armleo_gpio_mpw5 7576×1077615152, 10776 425.5 kBd83e33a0513d12dc99a7370bfcadaed0a581b6f9eb85e07cfde86e46b36f641f
B4 fabulous_efpga 7576×1077622728, 10776 984.9 kB9a70421302ebe4f38fbe2753c143e19dfa1966292a3bdfcaf06bfda053e23d9b
B5 i2c_controller 7576×1077630304, 10776 323.1 kB74ae3520ae39bb61bc69542f3b511fb90c9939d01e8fcaebf77ef10bbd468fb7
B6 lbist-mbist 7576×1077637880, 10776 436.8 kBe31664b83ced867c5a8b66196a41edb22538e11de3f64fa64f4ad17cc06502e0
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 476.2 kB63ca1d0045d07a6ce2645c0290d6c26b802f7ddf71fb727a3707c3934ed76329
C1 riscduino-qcore__q0_ 7576×107760, 21552 469.6 kB5ef09b7a4f17be9bf1c414b2d13c67a04be4ce6485c2f6a8fbe089e91e9fc4eb
C2 high_speed_vco 7576×107767576, 21552 293.6 kB9805672432a6f4bef828aea772299c621a4d72053d6e2fae18dcfe05299bd81c
C3 openfasoc-cryo-gen 7576×1077615152, 21552 385.4 kB588ef5a53249a6ce7b62403dff8f11e150c1c612735a3c5f72a474ba6a4de3f7
C4 microwave_signal_generator 7576×1077622728, 21552 336.4 kB0a3ffce6fe2a7421595a82d9d895c4709599b9255c1288e7390b5f51955f922c
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 344.4 kB576f4001e14638f9cc986ea84d639c5796c709840385ea21e165b91df7120a0a
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 299.7 kB56e72e8e636a419f9e024156147bcfc3ac672f85b6e1b335de3f0e1c8dd5991f
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 294.2 kBb39ce0675ccafef01abe786650c62ac892a581d5b37eee680e57b9c6efe00ef5
D2 azadi_iii 7576×107767576, 32328 599.0 kB1e5defdd57cd61e0b41ff52006fbe5677aa811a87806c8dfb92755b0729fbf8a
D3 tia_for_physic_experiments 7576×1077615152, 32328 296.6 kB6f96ccc6b5daf0c5d6d37cf7f18b50815d84ef45c480984c06e6ededb575c1f0
D4 qf105 7576×1077622728, 32328 442.6 kB6f494c9908c5af6b1c01b49f7c2dcf3b3bd47a4852820c430433b3006a0f8dd1
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 354.1 kBc94ee7766020269da86ef60918a6a6e6cc2fefd07b62fd81cdf3c9bdc8825f9d
D6 junga_soc_mpw5 7576×1077637880, 32328 360.1 kBae40de7ebfc146143c248f2cae119c47e7be3e65450c2224482009cae002fb5e
D7 nand_flash_mpw-5 7976×1077645456, 32328 318.3 kB1d28e47a9e4bd767bf86fa0d9b386afa7e6c54abf41b8118920c391edebe1dd0
E1 kasirga-c0-mpw-5 7576×107760, 43104 392.7 kB0a4156e6c8c5c5a4e723b8c3f66dbde9c3f496fb590af2fdb839b19a7058b334
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 383.4 kB947060bb386c817f6db4c99a4fa299f4ef47581fe5b87a797a6fc536f82fcb40
E3 wirelessenergyharvesting 7576×1077615152, 43104 318.4 kB19fc8c80529969c9b15117e59f36af927cb8daa36dbeabb928891885afeccd6f
E4 caravel_raster_engine 7576×1077622728, 43104 370.6 kBf2c54abb4ca6b769715fb5f472464acb836ffc4e63b952c79e81aa20765e0f9d
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 294.8 kB2d32a87ca8a735f6d27639db99da4d7d44d988d4ae1c185d94c42eeba43f8836
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 334.1 kB170c60e6be4c6631eef0e1f227498f003b49f2e06ac356e0710badfe26d46ac3
E7 alu 7976×1077645456, 43104 329.3 kBa51cd115653b15b49bc5b41e81231deeb23e2e60a49a875cb50ea60ce79045cf
F1 4ft4 7576×111760, 53880 343.3 kBc46c78b5621a2d659df01f3386210dfe5d27a3b1ac7f8d86962012d040d5ac70
F2 rng_chaos 7576×111767576, 53880 318.4 kBe3ba068907595ec52165ace7a2ecec4f88ffa04dcda2d33600f00e9a9cc91bfc
F3 uetrv-ecore 7576×1117615152, 53880 394.8 kBeb6af950a55119221f158c5894472f6709bc7498345d66177c9fde5a8c9583cd
F4 systolic_array 7576×1117622728, 53880 332.3 kBd2d76e20ecf66a0575be403be22771b696b8f90ac1f40104420ea59d9a8a86a0
F5 reram_test 7576×1117630304, 53880 296.3 kBc0a335c5a3cd2838617270bd3196e1a6ad779bd5eea95d4776827435b345880d
F6 secure_memory 7576×1117637880, 53880 341.6 kB70850205a44060ab1efeed9ed376a01c5d4208008c662e172c70d70992a10114
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 334.0 kBaa2c70bde5dd8806b66181ff01588818889a0b97721a5b8c62b73a78adb41419

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 VIM3 on mpw-005

Resolved: reticle 5CS8011AC, run mpw-005, mask VIM3

Mask layer
VIM3 — Via3-PLM
Process step
144 — Via3 mask
Drawn layer
70:44
Layer on the mask-layer GDS
50:0
Also
Via 3 (M3→M4)
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.