Download code/tt_meteor/tt/kernels/ktile_reader.cpp from changh95/meteor-p150: direct link, hf CLI and curl.
- Browser
- Download file 5.51 kB
-
https://huggingface.co/changh95/meteor-p150/resolve/main/code/tt_meteor/tt/kernels/ktile_reader.cpp
- Command line
-
hf download hf://changh95/meteor-p150/code/tt_meteor/tt/kernels/ktile_reader.cpp
-
curl -L -o ktile_reader.cpp https://huggingface.co/changh95/meteor-p150/resolve/main/code/tt_meteor/tt/kernels/ktile_reader.cpp
5.51 kB
| // SPDX-License-Identifier: Apache-2.0 | |
| // KTILE reader (meteor-p150 OPT2, tt/ktile.py): a ROW_MAJOR map (logical [A, B, WD, C], one DRAM page per pixel of | |
| // PAGE = C * ES bytes) tilized into the TILE form of the same logical shape, without a compute kernel. | |
| // Work units (no per-core RT args, probe P3: core i = y * GX + x of the first NC cores owns the contiguous unit range | |
| // [i * Q + min(i, E), + Q + (i < E)) of the NU = A * B * XB units, Q = NU / NC, E = NU % NC): unit v = 32-pixel row | |
| // block xb = v % XB of plane v / XB, pixels p0 = (v / XB) * WD + 32 xb, n = min(32, WD - 32 xb) valid rows; its | |
| // output = the CT tiles v * CT + 0..CT-1. | |
| // Per unit: the n pixel rows read as NBANK runs of same-bank consecutive pages (rows j, j + NBANK, ... of one DRAM | |
| // bank; staging slot of row i = (i % NBANK) * 32 / NBANK + i / NBANK) into a double-buffered L1 staging area (CB 1), | |
| // the next unit's runs issued while this unit is tilized; tilize = 16-element face rows (16 * ES bytes) copied by | |
| // stateful local NOC reads into the CT tiles of CB 0 (tile k, face 2 (i / 16) + h, face row i % 16 <- row i, | |
| // elements 32 k + 16 h); the rows n..31 and the channel halves >= C zeroed (the tilize padding). | |
| // Crop (a window of a larger 4-D map): the source page of output pixel j of plane q is SRC_OFF + q * SRC_PSTRIDE + j | |
| // (no crop: SRC_OFF 0, SRC_PSTRIDE WD). | |
| // CT args: [0] NU, [1] NC, [2] GX, [3] XB, [4] WD, [5] C, [6] ES, [7] NBANK, [8] CT, [9] SRC_OFF, [10] SRC_PSTRIDE, | |
| // then the TensorAccessorArgs of the input. Common RT args: [in_addr]. | |
| constexpr uint32_t NU = get_compile_time_arg_val(0); | |
| constexpr uint32_t NC = get_compile_time_arg_val(1); | |
| constexpr uint32_t GX = get_compile_time_arg_val(2); | |
| constexpr uint32_t XB = get_compile_time_arg_val(3); | |
| constexpr uint32_t WD = get_compile_time_arg_val(4); | |
| constexpr uint32_t CH = get_compile_time_arg_val(5); | |
| constexpr uint32_t ES = get_compile_time_arg_val(6); | |
| constexpr uint32_t NBANK = get_compile_time_arg_val(7); | |
| constexpr uint32_t CT = get_compile_time_arg_val(8); | |
| constexpr uint32_t SRC_OFF = get_compile_time_arg_val(9); | |
| constexpr uint32_t SRC_PSTRIDE = get_compile_time_arg_val(10); | |
| constexpr auto in_args = TensorAccessorArgs<11>(); | |
| constexpr uint32_t PAGE = CH * ES, TB = 1024 * ES, FACE = 256 * ES, FROW = 16 * ES; | |
| constexpr uint32_t RUN = 32 / NBANK; | |
| constexpr uint32_t cb_t = 0, cb_stage = 1; | |
| inline void unit_rows(uint32_t v, uint32_t& p0, uint32_t& n) { | |
| const uint32_t xb = v % XB; | |
| p0 = SRC_OFF + (v / XB) * SRC_PSTRIDE + xb * 32; | |
| n = (WD - xb * 32) < 32 ? (WD - xb * 32) : 32; | |
| } | |
| template <typename TA> | |
| inline void read_rows(const TA& src, uint32_t p0, uint32_t n, uint32_t stage) { | |
| for (uint32_t j = 0; j < NBANK && j < n; ++j) { | |
| const uint32_t cnt = (n - j + NBANK - 1) / NBANK; | |
| noc_async_read(src.get_noc_addr(p0 + j), stage + j * RUN * PAGE, cnt * PAGE); | |
| } | |
| } | |
| inline void zero(uint32_t addr, uint32_t bytes) { | |
| volatile tt_l1_ptr uint32_t* q = reinterpret_cast<volatile tt_l1_ptr uint32_t*>(addr); | |
| for (uint32_t w = 0; w < bytes / 4; ++w) { | |
| q[w] = 0; | |
| } | |
| } | |
| void kernel_main() { | |
| const uint32_t core = get_absolute_logical_y() * GX + get_absolute_logical_x(); | |
| if (core >= NC) { | |
| return; | |
| } | |
| constexpr uint32_t Q = NU / NC, E = NU % NC; | |
| const uint32_t u0 = core * Q + (core < E ? core : E); | |
| const uint32_t nu = Q + (core < E ? 1 : 0); | |
| if (nu == 0) { | |
| return; | |
| } | |
| const auto src = TensorAccessor(in_args, get_common_arg_val<uint32_t>(0), PAGE); | |
| cb_reserve_back(cb_stage, 1); // reader-private, never pushed | |
| const uint32_t stage0 = get_write_ptr(cb_stage); | |
| const uint64_t here = get_noc_addr(stage0); | |
| uint32_t p0, n; | |
| unit_rows(u0, p0, n); | |
| read_rows(src, p0, n, stage0); | |
| noc_async_read_barrier(); | |
| for (uint32_t v = u0; v < u0 + nu; ++v) { | |
| const uint32_t stage = stage0 + ((v - u0) & 1) * 32 * PAGE; | |
| cb_reserve_back(cb_t, CT); | |
| const uint32_t wt = get_write_ptr(cb_t); | |
| if constexpr (CH % 32 != 0) { // the last tile's upper 16 columns: channel padding | |
| zero(wt + (CT - 1) * TB + 1 * FACE, FACE); | |
| zero(wt + (CT - 1) * TB + 3 * FACE, FACE); | |
| } | |
| if (n < 32) { // the width padding rows | |
| for (uint32_t i = n; i < 32; ++i) { | |
| for (uint32_t k = 0; k < CT; ++k) { | |
| for (uint32_t h = 0; h < 2; ++h) { | |
| zero(wt + k * TB + ((i >> 4) * 2 + h) * FACE + (i & 15) * FROW, FROW); | |
| } | |
| } | |
| } | |
| } | |
| noc_async_read_one_packet_set_state(here, FROW); | |
| for (uint32_t i = 0; i < n; ++i) { | |
| const uint32_t s = stage + ((i % NBANK) * RUN + i / NBANK) * PAGE; | |
| const uint32_t d = wt + ((i >> 4) * 2) * FACE + (i & 15) * FROW; | |
| for (uint32_t k = 0; k < CT; ++k) { | |
| noc_async_read_one_packet_with_state(s + k * 32 * ES, d + k * TB); | |
| if (k * 32 + 16 < CH) { | |
| noc_async_read_one_packet_with_state(s + (k * 32 + 16) * ES, d + k * TB + FACE); | |
| } | |
| } | |
| } | |
| if (v + 1 < u0 + nu) { | |
| unit_rows(v + 1, p0, n); | |
| read_rows(src, p0, n, stage0 + ((v + 1 - u0) & 1) * 32 * PAGE); | |
| } | |
| noc_async_read_barrier(); | |
| cb_push_back(cb_t, CT); | |
| } | |
| } | |