mpw-006 / MM3 Metal 3-PLM

the MM3 shapes of all of mpw-006

40 of 40 dies rendered.

210,517,709 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 (193.2 MB in total, largest 7.6 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-006_MM3_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-006_MM3_reticle.png
the stitched reticle, full resolution
82.3 MB 632751098e41518ecebb112d7d502a5c7dfce576dd6bb974465ab582715bbe8c308f66d1 c0833b2d8783fd6da2a1e482602f2559645104dfc53699ff75bcdebdc2bcd9ed
mpw-006_MM3_reticle_overview.png
the same image scaled to fit 4096 px
5.0 MB dc4ed68a6232b5fa032af2d6f294011fc018b769f94bcf106a07a17f1b0094d4f355abaa 66085e20679add81910312a33c6ed09456ccf1f208fe23947053396d0051280b
mpw-006_MM3_tiles.json
where every tile belongs, and its checksum
13.6 kB 8bbc1cd98cecd9956a18a61ca8595cf9f28acb494579703798bbec91bafb9207f42eb72e 71db13199ccfa244dade2ca3b0b15a5b7c3e7f471ba97ec99daa6a21482194ba
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 free_and_open_source_silicon_implementation_of_aes 7576×107760, 0 4.0 MB7c83acb2f36392412e8dd06313ec7d4785438af77138c8a56110d49b221d1078
A2 microwatt_mpw6 7576×107767576, 0 7.6 MB04f407f895a06d52d0f998aed8cdc4adb338c5339065f76e10486fb63a7955ff
A3 hack_soc_-_mpw-6 7576×1077615152, 0 3.9 MB281d32cb213ec1c4b2fbb54b037912c8db239beddcbdea8fd27bb5fd6c90dc8c
A4 riscduino-dcore_d3_ 7576×1077622728, 0 6.5 MB5689295febf0d8fc4bb6aa3b373758bc74c1db0af084494ba18defc9eac03556
A5 riscduino-qcore_q2_ 7576×1077630304, 0 7.5 MB6cf854aa4625349edc6c17a81e463de3392cf6c31607f8e176296fbc1fb2461b
A6 riscduino-score-s4-2 7576×1077637880, 0 6.1 MB00ed6e67ec56e4a9c2027db839052975f0adc1ce054a3e56a318222a0509a283
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 5.8 MBe74542720f097c914c737a4e2a6cc96cab328bb580bff0dce6c8670301382680
B2 ft8_receiver_test 7576×107767576, 10776 3.7 MB00ca2e2da0a6e3755e822567fb210335ebc980323efbac7c9358502feecec127
B3 azadi_iii_dft 7576×1077615152, 10776 5.7 MB8985b9154e8ff9654218b1d7e8aa14c72c096fe6897794ec7071b170d569de7d
B4 sramtestvehiclesequel 7576×1077622728, 10776 3.6 MBcb79a9da6cd7b4ce99ab243335bb957f7d3d76d4d6236ab4a7621231f8805a74
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 4.5 MB66fcc983eeec3d6602d838ee3774bfc362edc2c2011811cd04457e9d2cf5ce2a
B6 asicle-ro 7576×1077637880, 10776 4.9 MB6f8be66d20adb7d3d3f72f6200b8343ce5bc526621ccdec8203fa277723c511e
B7 10b_adc_and_analog_support 7976×1077645456, 10776 3.8 MB893252cfe6d347896eaba9ba9683aac49604f3e14176cd1094990ba9952f13e2
C1 yonga-modbus_controller 7576×107760, 21552 4.1 MB201e6586f23a62db49149e2b87bcaf4df9662dda2331cd102ac501d9a71c365a
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 4.3 MBcce7566a70a79b68d76804c341d0c869c35a5c5b1e02f1a32eee2782566679dc
C3 openram_test_design 7576×1077615152, 21552 6.3 MBc1a846d1de2251e45bb00126a5dd660e0551300b9a747dd41675f5219864c937
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 4.6 MB3b16a7e5414995976fc3b0ecc6a6ce9c9dd898567c3d436a6403da9fc7362406
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 4.2 MB8327550565d1d37448e7971154feaf9c97efbca2f154adafec1f49dfa7e3cdf8
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 4.2 MBdfce35ebd5fd70417a1a4320cb3a470d294a177b4ce9a4ca9beef996a8ed34d1
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 3.7 MBbe6fe1d1c9b27c33bbcc4dfc85bd8aead88a45df84e4467fc377242e380efd1a
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 3.7 MB9d6f6feee450574c57a85103c92f2d5dbd7a7fccfd4d6ec7195c059e828c9c09
D3 order_prga_mpw6 7576×1077615152, 32328 6.3 MB9bc07d3c510f5a8fb4fd3d84ff1ab41dd993e5635034646c49330de6a28d7759
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 4.1 MBfead5de7893aa28210c0e25bf70e0540baa16363eca537e79eca10213eb299d3
D5 large_memory_micro 7576×1077630304, 32328 6.1 MBbe6c4893dd1b21cb64e335b5b747ca9b2807e9a8bbb1dc43f28289672d96a234
D6 rng_chaos_scroll 7576×1077637880, 32328 4.2 MB436864437fbd1bc1879c280b2630ae57f6bbb65dca2e9819216de484b913208f
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 3.7 MB43c9e39aa0e4e417b331cd65f4217db74745fae16ac27da3852dc6c77af62186
E1 mixed_signal_circuits_v2 7576×107760, 43104 3.6 MBb6f70afe2dc12578ac35a2659e1f05a98729a42008571c0d53d280b818b3fd55
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 3.6 MBcad820c42a94e69374956239a11573fbcb5bb912fadfff85da6b1092b5794ed3
E3 floating_point_halfprecision 7576×1077615152, 43104 4.2 MB16030f6731138049a8b76531d4d8ca27e24e3030919df1e4ce8f0d83f323e9c9
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 4.2 MB00f94f552047891b3607fa118df2afd28b56cb0ebc2a8484757f94b4343c9f83
E5 floating_point_unit_single_precision 7576×1077630304, 43104 4.3 MB241529a33bab855461d92d879fc9df4f8f0e2949f9d0aed54093cbb6293af5be
E6 experiar_soc 7576×1077637880, 43104 6.6 MB238209e23887c0a914c3aee0d20e9573cf10baceae9f5e52c139dfda7ff4f889
E7 my_caravel_analog_project 7976×1077645456, 43104 3.7 MB89eebec98eba9a076b45b057ac6e3d9e84257ef6105047d21227629ca3997699
F1 efabless_mpw6_riscduino 7576×111760, 53880 6.6 MB74aee1c8aab1e79264bcbace7063419baf7ca7ef9628ae1220a2e2401930463b
F2 motius_pong 7576×111767576, 53880 4.0 MB381016b361042106f1628a3d7c2e443b963acfcc89eae3a69ea2e1320c5f1bab
F3 soc_now 7576×1117615152, 53880 4.3 MB1f4aab73fc6cfc089d52f47a31411f4bf04145a293c41bc293135262edb409b2
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 6.3 MBecb470dea637637813806ae8c98de8bc94d20f48c2f31471caeeccb3dcadc20a
F5 optimised_strong_arm_latch 7576×1117630304, 53880 3.7 MB76c2591bc724665eb87f8946174a115faffce81190ce74ed194c78f74733e550
F6 riscduino_qcore_folk 7576×1117637880, 53880 7.3 MB662216e2b1633674634afe20e8e8b42e2490364129adff3c701fb961d5743fd0
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 3.9 MB85bbd0c8299b40a2988e4adb71806516be29b63a5a884ba62722a84cb3c00e98

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 MM3 on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask MM3

Mask layer
MM3 — Metal 3-PLM
Process step
139 — Metal3 mask
Drawn layer
70:20
Layer on the mask-layer GDS
34:0
Fill layer
34:28
Variants
Metal 3-TLM, Metal 3-S8TM, Metal 3-PLM
Also
Metal 3
Used in SKY130
yes

mpw-006 — SKY130 MPW-6

Foundry product
EF MPW#6 (+ 'With ReRAM' split lot)
Reticle set
5CS8014AC
Run date
2022-04-11
Submissions closed
2022-06-08
Projects
85
Fab lot
Identification
confirmed — Lot records: EF MPW#6 ('Held pre-mask' in late 2022; MPW-6 taped out 2022-12)
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-6 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-006/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.