mpw-006 / VIM4 Via4

the VIM4 shapes of all of mpw-006

40 of 40 dies rendered.

10,150,899 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 864.8 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-006_VIM4_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_VIM4_reticle.png
the stitched reticle, full resolution
11.9 MB f79c34296e8664a776564e04ae9c3aac0c51268384f627db4f5ad435064659e43c93e0cd 76188c69bd911212093488c32f5f4e3a779f349670d645985ecba0dc24fa86d0
mpw-006_VIM4_reticle_overview.png
the same image scaled to fit 4096 px
610.9 kB 9f115aab2b5d74a315568b6b7ca60608086c58da0150142a474d8e1ea4d645afece03bea 8543d89b880cae5fb40e87a30a174c73885d1c45a377dd7ec4781b8bbfd9251f
mpw-006_VIM4_tiles.json
where every tile belongs, and its checksum
13.6 kB 92716190b9842420cab6f0364d785a68d0a9835565e3a20117586d5ebf2618b58ef2beda f23451724671041f1e76d1c036f830d7829c8cd686b8fe4dbab004e9387e434d
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, 0 731.2 kBf43d9da79ee8df45a55852eb5eb94fca13258ec8250a051efb83b6b4169ff433
A2 microwatt_mpw6 7576×107767576, 0 726.4 kB45a99dc795614a9d53174355c30df57161b23e1c06dc16b631539a862bb29417
A3 hack_soc_-_mpw-6 7576×1077615152, 0 730.8 kB59b52fdb58fe5be4e08d44f8f3aad7201358c98064a3946a4e02f305c6dd305c
A4 riscduino-dcore_d3_ 7576×1077622728, 0 760.2 kBa501468341c5a6240088285d90deb69c922f5927f38c03555c035c918c18bafb
A5 riscduino-qcore_q2_ 7576×1077630304, 0 767.7 kBfd5d86387db0f0ef4b3f5a1798451d33d60b6f48c7da596d5ddb60f03a93d133
A6 riscduino-score-s4-2 7576×1077637880, 0 757.5 kB1a575614c740dbe530a8b00cdc5c940d1e5d8b993094ce8b202ff125ab7f98d5
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 721.9 kBfe02140a8b1a4430263be006ca3a005620bd551688be5da8cd6897b0850f7e5e
B2 ft8_receiver_test 7576×107767576, 10776 678.7 kB40ab096843c2c910ce661a024b089ccd7c5537187a41522468852f3ca6175758
B3 azadi_iii_dft 7576×1077615152, 10776 720.5 kBbd705bb3b00fd0f6f647beb2a62c61cfa896df3a981a84f597f560b35b5e79df
B4 sramtestvehiclesequel 7576×1077622728, 10776 669.8 kB208dd99595e95abd691d00cab105987c33cfd3a0e60190b211eaaa93fe0cd64e
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 728.9 kBa1f6c8a16ab4807728bb5274943d7f397c0accca88679d0c6bbc94aa60c03a66
B6 asicle-ro 7576×1077637880, 10776 730.4 kB4051927c6070e836dca03a562e8103bcdceaa692c00633205fa22d20b17c1dde
B7 10b_adc_and_analog_support 7976×1077645456, 10776 864.8 kBe7fc2cf159d0fa67394c670f5c692304700fe577eeb6eaae51e3856d03e805ee
C1 yonga-modbus_controller 7576×107760, 21552 730.6 kBa3409c1e3456e3d3874e9a44ddd8282f608da54932321cacd20967d7e121592d
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 730.5 kB927550721478dd6b93f80f17cac07b8ab131a11fffc79a6f9e5a6f1d4af245b5
C3 openram_test_design 7576×1077615152, 21552 730.9 kBdc4f4f2b417a27447d195eb7f5a9f6c5a4f417f5dc2526786f48fd2f8e84d9f8
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 726.8 kB2711b2209b11abd7cc5ffa23fe6a47519295472513616cecc0f701db24a86241
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 730.5 kB4729285b78dbbe3dfcff2e9c3b6b2ed12b5a2df00580db49820accb5571c4624
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 745.2 kBb892024e5bd9ec1e34da8c1ff829ed906093f1a5b46c4382c7f606f5d99bfeef
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 671.9 kBbaf0a39e15011653482564b27c06919f28cfcfce39dfd5f2674a6291660d3bb2
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 671.5 kB8678b3633270f2d59238f8c527d1e27f9f1bc5714249831be60456a32d02991f
D3 order_prga_mpw6 7576×1077615152, 32328 723.0 kB51cd044a83dd2655404c058b49fe1acbd14ed8530ac113d40b0e4a31964a8e87
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 730.1 kB641723487e515e351434bcfce3ecf7772d2a608f408679dffd8d439e33f13a21
D5 large_memory_micro 7576×1077630304, 32328 760.1 kB69a515bf37d61cca27f7a536d71fbaf43686ec417125b281ad4f6d21097db821
D6 rng_chaos_scroll 7576×1077637880, 32328 731.0 kB16d93b02ba608c52f024f0c5568cc6aeab0d6551e69331ba0da538676511c2c5
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 685.6 kB4d2c172305afb93d5eb84c00a7dddf91501a165f530c8ce58410f3874405255c
E1 mixed_signal_circuits_v2 7576×107760, 43104 670.0 kB28cd618e7d372704472e8b105013da1693e825047f50142fd348b369c6757de8
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 671.7 kB6b8f076610d698e0af0336a6ba06419e404cc6402bbaf32b967b5450aba13466
E3 floating_point_halfprecision 7576×1077615152, 43104 729.5 kB9b2c3f3543e02198ade65d48f2ea4fcd95fd82c6ba2b6e6fdacb339baa40f2f9
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 730.3 kBb9bd0be2d00b2b7fabbe466336dbb462ae5d24737e55a2b3b3de77c482e96243
E5 floating_point_unit_single_precision 7576×1077630304, 43104 729.9 kBbd1b378baa167d51be99e772e39b5b6ceb364f3c9e8dce45fcc19d22e9eeb26b
E6 experiar_soc 7576×1077637880, 43104 723.5 kBa46e9bb5ccdf62af915dfcd2e748ac8ae2db70b8649385c03eec93f0e10594ac
E7 my_caravel_analog_project 7976×1077645456, 43104 857.0 kB9421a2d5e329a0f64f6387b5c64ba15080e53b7ce6bad2f5960ff6ec1232409d
F1 efabless_mpw6_riscduino 7576×111760, 53880 722.4 kB78a165be981b0e76e00f85b144aa414042722ffd6b6a24fc924b21ff837b1e69
F2 motius_pong 7576×111767576, 53880 735.5 kB72cad08143698a6ce4ceb444c403e3af4bcf7b2407532d0e5b264a48f2596496
F3 soc_now 7576×1117615152, 53880 734.2 kBfb44c9c0842739fcef6f580afc742ebcb1ecf9313c1b77ce1707217d8c9e2c4c
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 727.4 kB09a113cc28bbc3aa4e76e2d5fafde8d5ff28a655dae61de7dd73166fbed599c3
F5 optimised_strong_arm_latch 7576×1117630304, 53880 676.0 kB673349223e318c28acc2c02f02136309b5829f4348b71f415a4796fb20032505
F6 riscduino_qcore_folk 7576×1117637880, 53880 705.9 kB35dd7834a2d23683afd8c223c9dc67d493f420953ba817f7701512529ce96ff2
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 750.2 kB9eda84b12791efc34e636568b0778682eac671e7128d83e6dbbf3a6c32f0e56c

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 VIM4 on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask VIM4

Mask layer
VIM4 — Via4
Process step
159 — Via pad mask
Drawn layer
71:44
Layer on the mask-layer GDS
58:0
Also
Via 4 (M4→M5)
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.