mpw-004 / RRM RRAM mask

the RRM shapes of all of mpw-004

40 of 40 dies rendered, 38 with nothing on this mask.

9,349 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
B4 slot-010 tile
icesoc
(empty)
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 (4.4 MB in total, largest 149.8 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-004_RRM_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-004_RRM_reticle.png
the stitched reticle, full resolution
3.5 MB 2cabb266002d97da08f7600687276d3f0053f511feada368b31d50cdcfcf01564babbf4c 357500161f2eb00e66563eb6e599add3662aaf0739c9fcb42781359d13b9cb14
mpw-004_RRM_reticle_overview.png
the same image scaled to fit 4096 px
16.4 kB 5e1e877dd4601e911bf5f95f43af0a6656a5d4b86ec82dd616044ba56e38a029b3f522ca 96b5f0ca839c89b2dcbdd4c9c4c71e6acf961245136ff4217f38fcc1bba429e6
mpw-004_RRM_tiles.json
where every tile belongs, and its checksum
13.3 kB 5dc5d1924e42db24d3b1429861cfd56b549dcfdf7cf217599120d07dc1048450e7c0f052 5d403f879183642b5b6a8b68a2cd35851e26985d08531779cfee0337830a2ca3
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 zero_to_asic_course_group_submission_mpw4 7576×107760, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A4 pifive-soc 7576×1077622728, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A5 ram_generator 7576×1077630304, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A6 space_controller 7576×1077637880, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B2 4t1r_testchip 7576×107767576, 10776 102.9 kB6153ed863d561d934e0749412c8a422251bd08c221201bde3eff409fc0f6a1e9
B3 yonga-turbo_encoder 7576×1077615152, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B4 icesoc 7576×1077622728, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B5 key_value_store 7576×1077630304, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B6 subservient-mpw4 7576×1077637880, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B7 logic_bist 7976×1077645456, 10776 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
C1 riscduino-r1 7576×107760, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C2 template 7576×107767576, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C3 vexriscv_soc 7576×1077615152, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C4 ring_oscillator 7576×1077622728, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C7 approximate_multiplier 7976×1077645456, 21552 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
D1 icd_fast_nu_mpw4 7576×107760, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D2 rram_testchip 7576×107767576, 32328 149.8 kBb4365ccd2943f5ec1e5b4f2317305288d523c9a101fc3702e3a0ca7ab71b91ef
D3 rest 7576×1077615152, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D5 sky130_radtol_test_chip 7576×1077630304, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D6 two_stage_cmos_opamp 7576×1077637880, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D7 ks-guitar 7976×1077645456, 32328 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
E1 ks-guitar-2s 7576×107760, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E2 yifive_a2 7576×107767576, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E5 junga_soc_mpw4 7576×1077630304, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E6 ibtida-ii 7576×1077637880, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E7 azadi_ii 7976×1077645456, 43104 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F2 current_starved_vco 7576×111767576, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F3 updown_counter__test_ 7576×1117615152, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F4 skullfet 7576×1117622728, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F6 kasirga_k0 7576×1117637880, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F7 iotestvehicle 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 RRM on mpw-004

Resolved: reticle 5CS8010AC, run mpw-004, mask RRM

Mask layer
RRM — RRAM mask
Drawn layer
201:20
Detail
the RRAM-stack mask (r1c) of the sky130B RRAM tier between met1 and met2. One drawn layer r1c = GDS 201/20 (open_pdks names it RERAM, short alias 'rr' -> 'rr' + M) defines all three physical films: rr1_bot_electrode, rr1_oxide, rr1_top_electrode. Only on the later sets 5CS8016AC/17AC/18AC. sky130A designs draw no 201/20, so those slots render empty
Also
sky130B RRAM tier (met1-met2); drawn layer r1c = GDS 201/20
Used in SKY130
no

mpw-004 — SKY130 MPW-4 (original)

Foundry product
EF MPW#4 (+ 'With ReRAM' split lot)
Reticle set
5CS8010AC
Run date
2021-12-31
Submissions closed
2021-12-31
Projects
52
Fab lots
4216266
4216266
4216266
Identification
confirmed — Lot records: EF MPW#4, lot 4216266 = 'SKY130 MPW 4'; the set is absent from the 2026-08-25 return shipment (destroyed 2025-06) — see 5CS8018AC
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-4 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-004/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.