mpw-006 / LVTNM Low Vt Nch*

the LVTNM shapes of all of mpw-006

40 of 40 dies rendered.

143,791 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 (7.4 MB in total, largest 261.8 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_LVTNM_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_LVTNM_reticle.png
the stitched reticle, full resolution
5.4 MB d134b0169a2843425f2a12b1803895807ab2f3182c96ad77a31b2edcb4c7b919725b176a a789894ac1f765596ba5caa16c3893d7ff41f89178619c8ccb79fbba6d0a079f
mpw-006_LVTNM_reticle_overview.png
the same image scaled to fit 4096 px
432.5 kB 4288f0b52c42a8fdf8d9bbed4488d4528248bb49a3305296356acf337ef4891cc820af90 18e77d70026028433731b7e67626b4f67cb00b1174ac6a16390fe290b807c633
mpw-006_LVTNM_tiles.json
where every tile belongs, and its checksum
13.7 kB f05d244f5918bd53419493146a6a12b23005caddaca7a3b0db45a4f24ec1a39d00d4d8b7 519e39041015d031a5d80077a532442664d13e55356e95719cbcb2ef92b1d16f
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, 0 167.6 kB4539e79feb5a80801809d0ce492e8375d9f9e8dd49a2cbac9ef4768cbaaeccff
A2 microwatt_mpw6 7576×107767576, 0 200.8 kB158457eefe558c0807fa96e868aa76ee7cea8baccf744762e063755431a1c7a4
A3 hack_soc_-_mpw-6 7576×1077615152, 0 166.3 kBaa15a4c16d3647620950756859eaf62c753997cef3907edc1a1f6eb9464ab8e1
A4 riscduino-dcore_d3_ 7576×1077622728, 0 193.5 kBe0f1acd2ef3ea60e80addd159b4d6a5f3ecf64ba607dbb6258f9e928a950f8be
A5 riscduino-qcore_q2_ 7576×1077630304, 0 203.5 kB166812ad82f2967ab93e176abdcb2211633f71428b582e7f3b7c1dd113d48dea
A6 riscduino-score-s4-2 7576×1077637880, 0 190.1 kB83364bc60839a7f3d6e389f92d2a9af554113aa324221f3ac685d38c381691d2
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 175.5 kB9c276b67efca2f30d5a88ef20f478b591028f61de857f88209e5c65b1e9c2dcc
B2 ft8_receiver_test 7576×107767576, 10776 159.6 kBcd96eb6189a701585dfd94adbf5b5f5210f8c0a40361bcdf1d59f408e8a79ae2
B3 azadi_iii_dft 7576×1077615152, 10776 250.9 kB00f69075ede2637b695a903171ff6f3ecbc42bc4aaa68ba8f0873e0850794104
B4 sramtestvehiclesequel 7576×1077622728, 10776 159.0 kB8336a0596eb0900d274253a4ee3ee638a6511eea0d1c16c58732340cd4ff553d
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 166.6 kB6f4d3ac18f4d7f91bf38629d045be20a94b7c80058503b2d6a23ae1f96d68c32
B6 asicle-ro 7576×1077637880, 10776 170.9 kB1569051103ed6045a3eefc12cd2cfed415f66fdf73c76c575af4829ba66c6856
B7 10b_adc_and_analog_support 7976×1077645456, 10776 169.0 kBa76b086836d0d88b84483654111a329c16ff238b40ea7ce725012eec67063541
C1 yonga-modbus_controller 7576×107760, 21552 167.0 kB614dde71b4c15c1eeab84e626bbe774e42de6d6d9e7ab735e8f303d5d332aa61
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 170.2 kB73b1c17620c8abb6d914080758d5075d33ce53e7d36daeeeb698b0d3e08f7141
C3 openram_test_design 7576×1077615152, 21552 185.5 kBf3c87fb66c49a0296bc3cfa56686ee990cfadf166c611670e80d406db43f66df
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 168.6 kB21a04ec95b2b467c12ed5ae5989456d0a95b72eda987e63cb95f5a5fccbb9abe
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 169.5 kBfc4ee3fdfdec3da7bc13437868d80cafb6ceccb17ca1d36495614556367983a0
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 172.1 kB7ec83df01b38436af3c1b1ab50009905902f888a1c8911db2790a53e01ceb8f6
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 159.2 kB9fde6f8ec1cf112e5b0be5fece367f6bad1261eabd49b036c47fb2beb0ae7a47
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 159.0 kB8336a0596eb0900d274253a4ee3ee638a6511eea0d1c16c58732340cd4ff553d
D3 order_prga_mpw6 7576×1077615152, 32328 257.9 kBee8758d0d47cbf0d10f038d7318d037f763dd6ff02bc08b1ad83a0822eca99c0
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 166.3 kBd405e95025015223c1f3147921048e54b622439fafd48723799c520501440fa1
D5 large_memory_micro 7576×1077630304, 32328 174.0 kB0c42b1efda190061f1216fc5873d0d07397119c0a38e8399091bf8db76a8d54e
D6 rng_chaos_scroll 7576×1077637880, 32328 169.7 kB10fac0b17cc42ea9b741306be9823ca05351bec64c2c8626a94ce1c7fdf65c2c
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 162.7 kB73c86e6a4d7adac2f779331370516c77b690e46ff91ff5973099c7c1e5bcc0c8
E1 mixed_signal_circuits_v2 7576×107760, 43104 159.0 kB5030fe7b0ed99a84788adb9499267b63a251b83ee444cf7953b50fbdd446bfaa
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 159.0 kB8336a0596eb0900d274253a4ee3ee638a6511eea0d1c16c58732340cd4ff553d
E3 floating_point_halfprecision 7576×1077615152, 43104 169.5 kBc99255f3c1a12175af695448290348ebb6ad09a99ad64ec17ca5f918a3d2f5b8
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 168.3 kB00374e50ec454555d6247590979566f909c1200f3073a1662f45c049499ff909
E5 floating_point_unit_single_precision 7576×1077630304, 43104 168.7 kBdbde2b4dfda64eba3f049c322a84a4fc8ecc749d3063510c94358181a632da2c
E6 experiar_soc 7576×1077637880, 43104 185.4 kB1c12285f26cf7ce046f71837724f2c150c5966e8562da83a7ca9d764cd9c86d2
E7 my_caravel_analog_project 7976×1077645456, 43104 163.0 kB12025474a587e197b9e249bace55e9c2d8e115deda6ea965e9b1817400232ae5
F1 efabless_mpw6_riscduino 7576×111760, 53880 226.0 kB0baebea6957f51fa8f34405ec6e3f97c01cd4a50cb9033792efba69882ebe3eb
F2 motius_pong 7576×111767576, 53880 170.5 kBe122aff8e12d91153c9512a73fc248c1892c1bd0d17192ce9cab6c629cade39d
F3 soc_now 7576×1117615152, 53880 175.2 kB5984da742998cd5b6d8cfad92c9274359f005173509312bc4ed68251a8f779d7
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 261.8 kBd3dc2d8022089af6247b614b10b22e60feac1e4cdb0b370f638ac8af41f90e07
F5 optimised_strong_arm_latch 7576×1117630304, 53880 162.8 kB68677c03efb44f938334c3b98f38d5f74db23c39bf3bf77f2dbe460e453ac335
F6 riscduino_qcore_folk 7576×1117637880, 53880 203.8 kBa65d32f6c8a73681b91ce50da614183dc1dc99c1b96e3a9ce9b68c01b261ebe1
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 174.3 kB06eeee573cf5011541801f63a306c560776fb5c0e3bbc456058a8c889beebc07

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 LVTNM on mpw-006

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

Mask layer
LVTNM — Low Vt Nch*
Process step
14 — Low Vt NOMOS mask
Drawn layer
125:44
Derived from drawn layers as
125:44 OR (64:20 AND (78:44 OR 81:2))
Layer on the mask-layer GDS
25:0
Detail
drawn lvtn plus a created part [nwell AND (hvtp OR areaid.ce)] OR (LV nwell over varactors); only the drawn part is rendered
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.