mpw-002 / VIM2 Via 2-PLM

the VIM2 shapes of all of mpw-002

40 of 40 dies rendered.

39,043,609 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 (29.3 MB in total, largest 1.8 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_VIM2_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_VIM2_reticle.png
the stitched reticle, full resolution
21.9 MB ab3e79969c288f49ba083373780faea363c8dd949a756417fb44b609f7467f13c506fba1 4a1c65cc3d500ed3e8afeef98d7866297054741bf42c79e11e86c6138dc75f41
mpw-002_VIM2_reticle_overview.png
the same image scaled to fit 4096 px
806.6 kB 3faf0e8ba366832db89baffe1cbdcd8727be1f268a2b1ce5d53b2c9780480c2209883606 7649b42f1a0b6dc35494c839b643e23712e20c7b0a586e9667aec24af3c9511c
mpw-002_VIM2_tiles.json
where every tile belongs, and its checksum
13.3 kB ec6acb3e79e2717ad4f566510de21d18cd9598c853f8d0a047aa933a9770ba91f3717d4d c4e188fe8751790c21dbf23d6b3212b4d43238fa08433675183c5ccceac56910
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, 0 613.1 kBbcd9885c25a97d060b81b6cd354350d0373253e83abb85b6821cbb016e5153ca
A2 wishbone_can 7576×107767576, 0 742.3 kB8dad6acf4d9eb970236beaadf97a3f1e5a077aa2f6c9278e62fdac7a0742cb27
A3 Analog-Neural-Network 7576×1077615152, 0 472.3 kBab1532e6bcd274b5da31064d9fc28d72751098ecbe30787062a10eb10f19b3e4
A4 caravel_dsp2 7576×1077622728, 0 589.1 kB29de34a18eba3bca75a60727a2ba2461beee9b4c3ec7da80c423c6a7aaf12bb4
A5 eFPGA_v3_caravel 7576×1077630304, 0 1.7 MB1f749e98f605e7485bd18070ac096c985f4506b8791a099357fed7ada48fd96c
A6 opencryo_testchip 7576×1077637880, 0 472.5 kB8502ecbcddb85945f8f99e1e2a824402781d82cd3d9bd74d2e51255af43b1dac
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 631.2 kB333623a9a6538df878a8fe7c81631d5a08dec4ed265c28a33deddd2f1b39052c
B2 lexicon 7576×107767576, 10776 780.4 kBfef363ef2b1395f3566ffd28996a8b096631391cdbb384c10717f80cb08e19ea
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 652.3 kBb6681e90a528c1895e7eae0dc19c9166acd7860756c96f44bbed901f97d046de
B4 yonga-lz4_decoder 7576×1077622728, 10776 609.4 kB98dd77f889b5a13abb160d0c8b53bf2ca3387e9d2f810e3a5ef5bf3c0a136f5a
B5 Potentiometric_Digit 7576×1077630304, 10776 476.0 kBbd3bd60c11768be08870ac004c69a2cc753fc74689fb200476ca5d43d5702f09
B6 fuserisc_ver2 7576×1077637880, 10776 1.6 MB5ab440666bf66dd83e265eae65b3ffe3ab8d95dd9254298258ab713d02e8bb52
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 524.8 kBaadcbbcb2408119377f17ca25cad49b5cdfc7d61844177e2dfecd324da3de3ec
C1 Comparator_3v3 7576×107760, 21552 477.9 kB61bb1b8f622e875b0b393c60f95e3fb851cc21f2ead60cc0db0672e9b66ac3ca
C2 caravel_multi_encode 7576×107767576, 21552 598.6 kBe00cec1adf3ca23bd3af39dfc23e7386eaa8f1cf5cd27d2cc6f427469ff8a0f5
C3 kasirgalabs_uart 7576×1077615152, 21552 580.5 kBe14c7de1c467d74cfaf1f00035a32be5f7fba6a1c936be2e71cd71beb546bac2
C4 Automatically_genera 7576×1077622728, 21552 570.7 kBf12663eb06b40a3f0a842344d9f6d9ee85125f31ad3289c1ce5504ecfd14a7fd
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 1.0 MB1ba9d0b96f5b097eb1e2105b5ec8a053a0af5eede63a903d17991be2e306c583
C7 caravel_azadi_soc 7976×1077645456, 21552 670.2 kBf624a993387d17d4c387c25d764eefbec2afdaaf983be3a099fb605a3815c33a
D1 caravel_dsc 7576×107760, 32328 593.5 kB0087594233be4828e75edb9dc64d474fae77d35cc6ba9779fdceee7a87d55fa1
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 1.2 MB0213e4fd85897a13cac29c91bf2e91e012b4285e080fa87329b405ce6a4d8f00
D3 caravel_user_project 7576×1077615152, 32328 580.6 kBd5b5e1a22504c50ada070d07f02883e571b77f62c10d4835492ebfbbad32678d
D4 General_Purpose_Band 7576×1077622728, 32328 568.1 kB104d142f0230a5ab37c6692fcd08672a2ccdb0340d4c14b70ea82dfa2bc77b6f
D5 zero_to_asic 7576×1077630304, 32328 756.3 kB027bed604f5e21e7ae483857470c7f597778e0db68e5b3a8697bb493072972f4
D6 fast_gcd_for_large_i 7576×1077637880, 32328 1.8 MBc06de4ba39c7784698f5642982399dc519182b911fc73ecddf73821d62015568
D7 Columbus 7976×1077645456, 32328 484.3 kBdf756d33124aab878407da8b977f449321d519a466310ba051eaccb60dbc94fe
E1 Space_shuttle 7576×107760, 43104 825.3 kB0503ce8bfa7b9f9054d6f114b39f45938c59e352aa9190a6a148e8c07649f391
E2 subservient 7576×107767576, 43104 654.7 kBefad54a3d0e26b689d30b103091c48c9e090839cf2dd89e753ef60ecebaf72cc
E3 caravel_analog_fulgor 7576×1077615152, 43104 477.7 kB46afb0d8de1f2f4dbcb4fbf00d5ea800b4c59472a57c95d6048ff9e476e19625
E4 bandgap_reference_de 7576×1077622728, 43104 568.1 kB04389a5024eaba9d14c5883fd8472f637b5b1b51f7ab2cf87a07db747b0f6868
E5 renml 7576×1077630304, 43104 836.8 kBf5cb77f21c51f13ee45581e7cbb207f9356c1e83271c8b46897e0d23333df5aa
E6 io_expander 7576×1077637880, 43104 575.1 kB8b69c11f1628ada6d8fe91f0910a238b883b59f92e01df0452ed48d2cda16e96
E7 digital_pll 7976×1077645456, 43104 502.1 kB78f8d7129811602329fc7fd475182d4b671bbfff2a56674a7597e51f346934ad
F1 zero_to_asic 7576×111760, 53880 760.3 kBeca210c2ceabf904a23602782fd1b52bc04429076402d5eb9534ed25e28a3560
F2 caravel_fpu 7576×111767576, 53880 599.2 kB9eba3790159ba2071535d76c2496098e0be76be4cb58d2ec270986158f4c1cd5
F3 BrqRV_EB1 7576×1117615152, 53880 1.2 MBd8fe144293c6163f26b2d7d56404caeec3487cfd7aefe0d111f79e23f2749a88
F4 hilas 7576×1117622728, 53880 478.2 kB133b55f1667fa2c86c4b47c4888b64365ed2db39b27a565414117e616f92b6f1
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 475.7 kB51036ee68e16a6e1eeb6b80d6a4631b09dd6297d59dd61f422abf7a6a9dfcc34
F6 sha1_engine 7576×1117637880, 53880 706.1 kBb304873d0281430a35568bb47c61cb6149f146de75fae117386ebd2cbe2616d4
F7 caravan_openfasoc 7976×1117645456, 53880 697.4 kBb208ff72665f1b39c994bde89b9d7fd5933634e2667d76a8d477bdf4297febff

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 VIM2 on mpw-002

Resolved: reticle 5CS8007AC, run mpw-002, mask VIM2

Mask layer
VIM2 — Via 2-PLM
Process step
129 — Via2 mask
Drawn layer
69:44
Layer on the mask-layer GDS
44:0
Variants
Via 2-TNV, Via 2-S8TM, Via 2-PLM
Also
Via 2 (M2→M3)
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.