mpw-002 / PSDM P+ Implant

the PSDM shapes of all of mpw-002

40 of 40 dies rendered.

35,223,326 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 (80.0 MB in total, largest 5.9 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-002_PSDM_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-002_PSDM_reticle.png
the stitched reticle, full resolution
54.4 MB 1da448037b6922e56b4bc549f1bc83a58b026c8d341933651809565fa5a641640bb78b52 3a9c912356211e523088564419a9fdaf45106a349b0d25b309682a8437f50e0a
mpw-002_PSDM_reticle_overview.png
the same image scaled to fit 4096 px
2.4 MB ec7827379cd6295f2e7d6606e2074c38955371b7b2182c091b253690233bf12a4f6b950f ed7b126cffb91678823dd01eaa819f68b3592f91959e48099273abc1117d54bf
mpw-002_PSDM_tiles.json
where every tile belongs, and its checksum
13.3 kB 022c8fc75a09d7628b5343557c2783328a04dd47c8e66e2827b140547e070ef80bf83284 ff05488df5cdf0c4062cf3bf0084e921b93e88513d2bf6533680b8d6664c4219
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 axi_dma_using_spinal 7576×107760, 0 1.8 MB431e742c89e77cfc7769e5c20ba82c9cdd4b030c902e65d770b43d3c76fd2fd7
A2 wishbone_can 7576×107767576, 0 1.9 MB9793c83c3e00f19a7d1f4a80fa5de1e9ec7bf8ea03df56f42ecac3117ecbb53b
A3 Analog-Neural-Network 7576×1077615152, 0 1.2 MB7ec8a1bad81e7d85f4dfadf154e96a06eeb0083a1a1d60026c2096c443e3a4fd
A4 caravel_dsp2 7576×1077622728, 0 1.5 MBad731c1286dbe805b9568a704b269497dcf0d6263b4264b7fbf385efb197c7ac
A5 eFPGA_v3_caravel 7576×1077630304, 0 4.2 MB203a544b78f4672b1b155d10afdd681f6acceb1aa474d8baff5731a3455eeb61
A6 opencryo_testchip 7576×1077637880, 0 1.2 MB5bbe5ab8cfd365025ad1146da9f1eb11b965be3168bfcf38a0246ce5c53375c0
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 2.4 MBfdc18f061fa21d94875a69e3d3bbf55dbe5f66d8743a039398b58d9d0785df3a
B2 lexicon 7576×107767576, 10776 2.5 MB05a240d5ed78daa3b58933c0644a40bbb53dba798ac7b44b9235b5f034a20774
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 2.1 MB219eb7bea8e276d434cc0749f7a904c5118c1e4bacc91ad64279db41a6d61b4e
B4 yonga-lz4_decoder 7576×1077622728, 10776 1.5 MB3710dd98a7c4916711aa557f17ef12c8ea9d61a2a42588c1f4a3b292028353a5
B5 Potentiometric_Digit 7576×1077630304, 10776 1.2 MB9bb6014c5bed0d55281c6c117b42f865856c24fd8155c1063a49f4a52c3ee12f
B6 fuserisc_ver2 7576×1077637880, 10776 4.2 MBc21b2abb0798ec18a4cfd17a4447d9b342c1a0fbba37c65250d4cc847605ae75
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 1.3 MBc7952602ecd0c02a51261099669e5647478b9bf9348bac2384fb22f0ed7b9505
C1 Comparator_3v3 7576×107760, 21552 1.2 MBad8f745a783aeba44b28a7c0a7c9c0ad2d3b45e16ab8d6df042937b2079c895a
C2 caravel_multi_encode 7576×107767576, 21552 1.4 MBd2d027e9583310dda333a2b60e2eb06c8edfdff9f406b49705abdbbe1c39cf81
C3 kasirgalabs_uart 7576×1077615152, 21552 1.3 MBdc8e10dfc377357a7e5c1adf2a3385a22bd75fcc7886bb1ddca6ca63ecc3f01d
C4 Automatically_genera 7576×1077622728, 21552 1.2 MB607babd3471c6b4a01e8f45f7365995ceb51d5e5395b89634e2bfc4ab1412a0e
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 3.6 MBe5b9ceb4f6bbf94e05a4fd3150be7f295522decec012fbe514bb8b80c365c788
C7 caravel_azadi_soc 7976×1077645456, 21552 2.7 MBe2599d4f73421eff057ddd8a28376918c1913a010a33ca6d48cee6d05a3caee5
D1 caravel_dsc 7576×107760, 32328 1.6 MB1bdba3d57201a7df9329a978247420d0b5f31bf7374d24d8e229979d68d4bdb0
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 3.1 MB758a3debff76bf3463b6a056494fef8c3ddae5164752a9010ca82e161784d50f
D3 caravel_user_project 7576×1077615152, 32328 1.3 MB88c2303da35793f95945d8d3a5ee96d38bde0d4109239e8ad678fc82b4967ff5
D4 General_Purpose_Band 7576×1077622728, 32328 1.2 MBcc55389b0be61e9589516f379cf8348e7e696aa98c763138f95b3148e3aade0d
D5 zero_to_asic 7576×1077630304, 32328 1.8 MB4cc564058c4de4ee217c793439300f76e8a46d78dc1af81c12086b109be75ab4
D6 fast_gcd_for_large_i 7576×1077637880, 32328 5.9 MB9350cbeabc139a5e81d08cc838f7425b1d8809f94ea8dd365894e0b006391878
D7 Columbus 7976×1077645456, 32328 1.2 MB20b41c87658888b71252599431a89e8d930d30dc7c0e9e86b9b4a3cf4c63e4d6
E1 Space_shuttle 7576×107760, 43104 2.3 MB1d4d22ec916063421e6b76545e89043ff487a7bfa537023214b6e7dd0b966d9d
E2 subservient 7576×107767576, 43104 1.5 MBed7394f06f263abbe40bd71b38bf89bb2cf5cac0431aff9915ecace0fe575d9d
E3 caravel_analog_fulgor 7576×1077615152, 43104 1.2 MB294095541a7d3ca45aac81b0f1b609d91a41d1786b47575631149a8444fe69ee
E4 bandgap_reference_de 7576×1077622728, 43104 1.2 MB41e1afaf83e6e68874f4133aa7441a5248e87b0bdc6d2c78500298855e11dfa2
E5 renml 7576×1077630304, 43104 3.1 MBdb94092df712f225e5d0a1cf0292758034a0f0c6ca80980a6208a0cb2091940f
E6 io_expander 7576×1077637880, 43104 1.2 MB1fcab801ec66c97bdbdbd1533abfb5684d02ec761d15666f8c5d5faafdc1797a
E7 digital_pll 7976×1077645456, 43104 1.3 MBe3985b41952f801a16a6fa37d42d4127510ff06b487b279e8e3b2a0e7fe47f84
F1 zero_to_asic 7576×111760, 53880 1.8 MB58668b6621f8f2a46be4866a4df4e2e56e4ff05a3455fd70c8f2f5aaa3f3e5f6
F2 caravel_fpu 7576×111767576, 53880 1.5 MB3ae3ab56d89d896cf32f574bcb277882db75cd637c99d052dcb4ec525c930760
F3 BrqRV_EB1 7576×1117615152, 53880 4.1 MB0dddf88ff17afe24616b929e1af9a56ffa9c6c79b11a279c8dca704146fa03fe
F4 hilas 7576×1117622728, 53880 1.2 MBd4f92da23f89bccb2355ed6490b6af50fc453e1bc7018318507dcd4410907cb8
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 1.2 MBef1d8f5b43482e66e230d26b7d9518d4d3864f71734f54cd78bb8fb591ada916
F6 sha1_engine 7576×1117637880, 53880 1.6 MBf8f193d037a38380f0096714d2f8e0f402cc6dd799639049be6dda3c67e619b1
F7 caravan_openfasoc 7976×1117645456, 53880 2.2 MB36ccb8d74182beee648ae9aad544a42bcc8711969200d87f5f0bda0b8848d2e3

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 PSDM on mpw-002

Resolved: reticle 5CS8007AC, run mpw-002, mask PSDM

Mask layer
PSDM — P+ Implant
Process step
81 — P+ source drain implant mask
Drawn layer
94:20
Layer on the mask-layer GDS
32:0
Detail
PSDM = psdm OR grown psdm over pnp emitters
Used in SKY130
yes

mpw-002 — SKY130 MPW-2

Foundry product
EF MPW#2
Reticle set
5CS8007AC
Run date
2021-06-18
Submissions closed
2021-06-18
Projects
56
Fab lot
4205819
Identification
confirmed — Lot records: EF MPW#2, lot 4205819 = 'SKY130 MPW 2'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-2 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-002/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.