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dp global_swap with displacement constraint

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This commit is contained in:
bunchgrape 2025-05-02 15:43:42 +08:00
parent 649f320384
commit bc5a0323dd
5 changed files with 76 additions and 9 deletions
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4
cpp_to_py/gpudp/PyBindCppMain.cpp
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@ -110,8 +110,8 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
});
m.def(
"globalSwap",
[](std::shared_ptr<dp::DPTorchRawDB> at_db_ptr, int num_bins_x, int num_bins_y, int batch_size, int max_iters) {
return dp::globalSwap(*at_db_ptr, num_bins_x, num_bins_y, batch_size, max_iters);
[](std::shared_ptr<dp::DPTorchRawDB> at_db_ptr, int num_bins_x, int num_bins_y, int batch_size, int max_iters, float displacement_region_ratio) {
return dp::globalSwap(*at_db_ptr, num_bins_x, num_bins_y, batch_size, max_iters, displacement_region_ratio);
});
m.def("independentSetMatching",
[](std::shared_ptr<dp::DPTorchRawDB> at_db_ptr,

2
cpp_to_py/gpudp/db/dp_torch.h
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@ -114,7 +114,7 @@ void fillerLegalization(DPTorchRawDB& at_db);
// Detailed Placement
void kReorder(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int K, int max_iters);
void globalSwap(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters);
void globalSwap(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters, float displacement_region_ratio);
void independentSetMatching(
DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int set_size, int max_iters);

6
cpp_to_py/gpudp/dp/detail_placement.cpp
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@ -4,7 +4,7 @@
namespace dp {
void kReorderCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int K, int max_iters);
void globalSwapCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters);
void globalSwapCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters, float displacement_region_ratio);
void independentSetMatchingCUDA(
DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int set_size, int max_iters);
@ -12,8 +12,8 @@ void kReorder(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int K, int ma
kReorderCUDA(at_db, num_bins_x, num_bins_y, K, max_iters);
}
void globalSwap(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters) {
globalSwapCUDA(at_db, num_bins_x, num_bins_y, batch_size, max_iters);
void globalSwap(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters, float displacement_region_ratio) {
globalSwapCUDA(at_db, num_bins_x, num_bins_y, batch_size, max_iters, displacement_region_ratio);
}
void independentSetMatching(

18
cpp_to_py/gpudp/dp/global_swap_cuda.cu
View File

@ -71,6 +71,8 @@ struct SwapState {
int max_num_candidates;
int max_num_candidates_all;
float displacement_region_ratio = 0;
int pair_hpwl_computing_strategy; ///< 0: for the original node2pin_map and
///< net2pin_map; 1: for node2net_map and
///< net2node_map, which requires
@ -351,6 +353,19 @@ __global__ void compute_search_bins(DetailedPlaceData db, SwapState<float> state
db.y[node_id],
db.x[node_id] + db.node_size_x[node_id],
db.y[node_id] + db.node_size_y[node_id]);
if (state.search_bin_strategy and state.displacement_region_ratio != 0) {
float dxh = opt_box.xh - (db.x[node_id] + db.node_size_x[node_id]);
float dxl = db.x[node_id] - opt_box.xl;
float dyh = opt_box.yh - (db.y[node_id] + db.node_size_y[node_id]);
float dyl = db.y[node_id] - opt_box.yl;
if (dxh > state.displacement_region_ratio * (db.xh - db.xl)) {
opt_box.xh = db.x[node_id] + db.node_size_x[node_id] + state.displacement_region_ratio * (db.xh - db.xl);
}
if (dxl > state.displacement_region_ratio * (db.xh - db.xl)) {
opt_box.xl = db.x[node_id] - state.displacement_region_ratio * (db.xh - db.xl);
}
}
int cx = db.pos2bin_x(opt_box.center_x());
int cy = db.pos2bin_y(opt_box.center_y());
state.search_bins[node_id] = cx * db.num_bins_y + cy;
@ -834,7 +849,7 @@ int compute_max_num_nodes_per_bin(const DetailedPlaceData& db) {
return max_num_nodes_per_bin;
}
void globalSwapCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters) {
void globalSwapCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int batch_size, int max_iters, float displacement_region_ratio) {
cudaSetDevice(at_db.node_size_x.get_device());
DetailedPlaceData db(at_db);
db.set_num_bins(num_bins_x, num_bins_y);
@ -852,6 +867,7 @@ void globalSwapCUDA(DPTorchRawDB& at_db, int num_bins_x, int num_bins_y, int bat
const float stop_threshold = 0.1 / 100;
state.batch_size = batch_size;
state.displacement_region_ratio = displacement_region_ratio;
int max_num_nodes_per_bin = compute_max_num_nodes_per_bin(db);
state.max_num_candidates = max_num_nodes_per_bin * 5;
state.max_num_candidates_all = state.batch_size * state.max_num_candidates;

55
src/detail_placement.py
View File

@ -498,7 +498,7 @@ def run_dp(node_pos: torch.Tensor, data: PlaceData, args, logger):
dp_handler(gpudp.kReorder, "K-Reorder 1", num_bins_x, num_bins_y, kr_K, kr_iter)
dp_handler(gpudp.independentSetMatching, "Independent Set Match", num_bins_x, num_bins_y, ism_bs, ism_set, ism_iter)
dp_handler(gpudp.globalSwap, "Global Swap", num_bins_x // 2, num_bins_y // 2, gs_bs, gs_iter)
dp_handler(gpudp.globalSwap, "Global Swap", num_bins_x // 2, num_bins_y // 2, gs_bs, gs_iter, 0)
dp_handler(gpudp.kReorder, "K-Reorder 2", num_bins_x, num_bins_y, kr_K, kr_iter)
del dp_rawdb
@ -506,6 +506,55 @@ def run_dp(node_pos: torch.Tensor, data: PlaceData, args, logger):
return node_pos
def run_dp_local(node_pos: torch.Tensor, data: PlaceData, args, logger, displacement_ratio = 0.1):
# GPU Detailed Placement
dp_rawdb = setup_detailed_rawdb(node_pos, False, data, args, logger)
num_bins_x = data.num_bin_x
num_bins_y = data.num_bin_y
kr_K = 4
kr_iter = 2
gs_bs = 256
gs_iter = 2
# use integer coordinate systems in DP for better quality
scalar = compute_scalar(get_ori_scale_factor(data))
# scalar = 1.0
def dp_handler(dp_func, func_name, *func_args):
logger.info("Start running %s..." % func_name)
start_time = time.time()
if scalar != 1.0:
# NOTE: we assume site_width is integer, so 1 / scalar should be an integer
logger.info("scale dp_rawdb by %g" % round(1.0 / scalar))
dp_rawdb.scale(round(1.0 / scalar), True)
dp_func(dp_rawdb, *func_args)
if scalar != 1.0:
logger.info("scale dp_rawdb back by %g" % scalar)
dp_rawdb.scale(scalar, False)
# commit lpos for legality check
torch.cuda.synchronize(node_pos.device)
logger.info("Start checking...")
if not dp_rawdb.check(get_ori_scale_factor(data)):
dp_rawdb.rollback()
logger.error("Check failed in %s. Rollback to previous DP iteration." % func_name)
return
logger.info("Check Pass. Commit solution...")
# update dp_rawdb for next step dp_func and update the final solution
dp_rawdb.commit()
commit_to_node_pos(node_pos, data, dp_rawdb)
logger.info("***** Finish %s, HPWL: %.6E Time: %.4f *****" % (
func_name, get_obj_hpwl(node_pos, data, args).item(), time.time() - start_time
))
dp_handler(gpudp.kReorder, "K-Reorder 1", num_bins_x, num_bins_y, kr_K, kr_iter)
dp_handler(gpudp.globalSwap, "Global Swap", num_bins_x // 2, num_bins_y // 2, gs_bs, gs_iter, displacement_ratio)
dp_handler(gpudp.kReorder, "K-Reorder 2", num_bins_x, num_bins_y, kr_K, kr_iter)
del dp_rawdb
return node_pos
def run_dp_route_opt(node_pos: torch.Tensor, gpdb, rawdb, ps, data: PlaceData, args, logger):
# NOTE: we suppose M1's prefer routing direction is 0 (horizontal)
if ps.enable_route and gpdb.m1direction() == 0:
@ -703,8 +752,10 @@ def default_detail_placement(node_pos, gpdb, rawdb, ps, data: PlaceData, args, l
draw_fig_with_cairo_cpp(node_pos, data.node_size, data, info, args)
torch.cuda.synchronize(node_pos.device)
dp_start_time = time.time()
if args.detail_placement:
if args.detail_placement and not args.timing_opt:
node_pos = run_dp(node_pos, data, args, logger)
elif args.detail_placement and args.timing_opt:
node_pos = run_dp_local(node_pos, data, args, logger)
torch.cuda.synchronize(node_pos.device)
node_pos = run_dp_route_opt(node_pos, gpdb, rawdb, ps, data, args, logger)
dp_end_time = time.time()