mpw-002 / VIMC Via 1 top, RRAM tier

the VIMC shapes of all of mpw-002

40 of 40 dies rendered, 40 with nothing on this mask.

0 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
B1 slot-007 tile
yiFive
(empty)
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
E5 slot-031 tile
renml
(empty)
E6 E7
F F1 F2 F3 F4
F4 slot-037 tile
hilas
(empty)
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 (4.4 MB in total, largest 110.7 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-002_VIMC_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_VIMC_reticle.png
the stitched reticle, full resolution
3.5 MB 01eef4b823b21528d26891dab8eafb063755f68ba19b6fbd3f860e34de109bdb02f31987 d8048f2fde017421b5a20479e4503c28cdcb46b02119bc5c269d87735f5f0806
mpw-002_VIMC_reticle_overview.png
the same image scaled to fit 4096 px
13.4 kB cfa656aac362cb1519e7d8eaf1d975f114435ab8e24d0da135cf67dd8248075a5521729f 99874058da241339384e1119622030e721bbd5c65dfbea7a6e81cc848eb27a6b
mpw-002_VIMC_tiles.json
where every tile belongs, and its checksum
13.3 kB 88c1788f75771e3d76842ed75d76f91ebcc2db9590b2e6134895c30345af11121945a73e 44fd97ccb878dd9fa8c2917beaf5d39d865a931c2beb20e2fd34ab6322f17074
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, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A2 wishbone_can 7576×107767576, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A3 Analog-Neural-Network 7576×1077615152, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A4 caravel_dsp2 7576×1077622728, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A5 eFPGA_v3_caravel 7576×1077630304, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A6 opencryo_testchip 7576×1077637880, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B2 lexicon 7576×107767576, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B4 yonga-lz4_decoder 7576×1077622728, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B5 Potentiometric_Digit 7576×1077630304, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B6 fuserisc_ver2 7576×1077637880, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
C1 Comparator_3v3 7576×107760, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C2 caravel_multi_encode 7576×107767576, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C3 kasirgalabs_uart 7576×1077615152, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C4 Automatically_genera 7576×1077622728, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C7 caravel_azadi_soc 7976×1077645456, 21552 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
D1 caravel_dsc 7576×107760, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D3 caravel_user_project 7576×1077615152, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D4 General_Purpose_Band 7576×1077622728, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D5 zero_to_asic 7576×1077630304, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D6 fast_gcd_for_large_i 7576×1077637880, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D7 Columbus 7976×1077645456, 32328 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
E1 Space_shuttle 7576×107760, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E2 subservient 7576×107767576, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E3 caravel_analog_fulgor 7576×1077615152, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E4 bandgap_reference_de 7576×1077622728, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E5 renml 7576×1077630304, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E6 io_expander 7576×1077637880, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E7 digital_pll 7976×1077645456, 43104 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
F1 zero_to_asic 7576×111760, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F2 caravel_fpu 7576×111767576, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F3 BrqRV_EB1 7576×1117615152, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F4 hilas 7576×1117622728, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F6 sha1_engine 7576×1117637880, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F7 caravan_openfasoc 7976×1117645456, 53880 110.7 kB4819853e853378d6bf252c7d9d89c4caedfec9d3b73e01c973cd666bce8783c6

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 VIMC on mpw-002

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

Mask layer
VIMC — Via 1 top, RRAM tier
Drawn layer
68:44
Derived from drawn layers as
68:44 AND 201:20
Detail
the second via1 mask of the sky130B RRAM tier (r1v). The RRAM splits via1 in two: the designer draws one 'via' shape, and mask generation separates it into via_bot (cviam = VIM) and via_top (r1v) wherever the via is enclosed by r1c. Rendered as via AND r1c. NOT CTM1/mcon, as once assumed: 8016/17/18 each carry a separate CTM1 plate (400), and 455 sits above MM1 (450) while mcon is below met1
Also
sky130B RRAM tier; r1v, the upper half of the split via1
Used in SKY130
no

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.