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Author SHA1 Message Date
CGH0S7
1a518cd3f6 Optimize average2: use DO CONCURRENT loop form 2026-03-01 00:41:32 +08:00
CGH0S7
1dc622e516 Optimize average2: replace array expression with explicit loops 2026-03-01 00:33:01 +08:00
CGH0S7
3046a0ccde Optimize prolong3: hoist bounds check out of inner loop 2026-03-01 00:17:30 +08:00
CGH0S7
d4ec69c98a Optimize prolong3: replace parity branches with coefficient lookup 2026-02-28 23:59:57 +08:00
CGH0S7
2c0a3055d4 Optimize prolong3: precompute coarse index/parity maps 2026-02-28 23:53:30 +08:00
CGH0S7
1eba73acbe 先关闭绑核心，发现速度对比：不绑定核心+SCX>绑核心+SCX 2026-02-28 23:27:44 +08:00
CGH0S7
b91cfff301 Add switchable C RK4 kernel and build toggle 2026-02-28 21:12:19 +08:00
CGH0S7
e29ca2dca9 build: switch allocator option to oneTBB tbbmalloc 2026-02-28 17:16:00 +08:00
CGH0S7
6493101ca0 bssn_rhs_c: recompute contracted Gamma terms to remove temp arrays 2026-02-28 16:34:23 +08:00
CGH0S7
169986cde1 bssn_rhs_c: compute div_beta on-the-fly to remove temp array 2026-02-28 16:25:57 +08:00
CGH0S7
1fbc213888 bssn_rhs_c: remove gxx/gyy/gzz temporaries in favor of dxx/dyy/dzz+1 2026-02-28 15:50:52 +08:00
CGH0S7
6024708a48 derivs_c: split low/high stencil regions to reduce branch overhead 2026-02-28 15:42:31 +08:00
CGH0S7
bc457d981e bssn_rhs_c: merge lopsided+kodis with shared symmetry buffer 2026-02-28 15:23:01 +08:00
CGH0S7
51dead090e bssn_rhs_c: 融合最终RHS两循环为一循环，用局部变量传递fij中间值 (Modify 6) 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 13:49:45 +08:00
CGH0S7
34d6922a66 fdderivs_c: 全量清零改为只清零边界面，减少无效内存写入 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 13:20:06 +08:00
CGH0S7
8010ad27ed kodiss_c: 收紧循环范围消除边界无用迭代和分支判断 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 13:04:21 +08:00
CGH0S7
38e691f013 bssn_rhs_c: 融合Christoffel修正+trK_rhs两循环为一循环 (Modify 5) 
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 12:57:07 +08:00
CGH0S7
808387aa11 bssn_rhs_c: 融合fxx/Gamxa+Gamma_rhs_part2两循环为一循环 (Modify 4) 
fxx/fxy/fxz和Gamxa/ya/za保留在局部标量中直接复用于Gamma_rhs part2，减少数组读写

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 11:14:35 +08:00
CGH0S7
c2b676abf2 bssn_rhs_c: 融合A^{ij}升指标+Gamma_rhs_part1两循环为一循环 (Modify 3) 
A^{ij}六分量保留在局部标量中直接复用于Gamma_rhs计算，减少Rxx..Ryz数组的额外读取

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 11:02:27 +08:00
CGH0S7
2c60533501 bssn_rhs_c: 融合逆度规+Gamma约束+Christoffel三循环为一循环 (Modify 2) 
逆度规计算结果保留在局部标量中直接复用，减少对gupxx..gupzz数组的重复读取，每步加速0.01秒

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-28 10:57:40 +08:00
CGH0S7
318b5254cc 根据组委会邮件要求更新检测脚本，增加对3D向量和三个分量分别检测RMS小于1.0% 2026-02-27 17:38:21 +08:00
CGH0S7
3cee05f262 Merge branch 'cjy-oneapi-opus-hotfix' 2026-02-27 15:13:40 +08:00
CGH0S7
e0b5e012df 引入 PGO 式两遍编译流程，将 Interp_Points 负载均衡优化合法化 
背景：
上一个 commit 中同事实现的热点 block 拆分与 rank 重映射取得了显著
加速效果，但其中硬编码了 heavy ranks (27/28/35/36) 和重映射表，
属于针对特定测例的优化，违反竞赛规则第 6 条（不允许针对参数或测例
的专门优化）。

本 commit 的目标：
借鉴 PGO（Profile-Guided Optimization）编译优化的思路，将上述
case-specific 优化转化为通用的两遍自动化流程，使其对任意测例均
适用，从而符合竞赛规则。

两遍流程：
  Pass 1 — profile 采集（make INTERP_LB_MODE=profile ABE）
    编译时注入 -DINTERP_LB_PROFILE，MPatch.C 中 Interp_Points
    在首次调用时用 MPI_Wtime 计时 + MPI_Gather 汇总各 rank 耗时，
    识别超过均值 2.5 倍的热点 rank，写入 interp_lb_profile.bin。

  中间步骤 — 生成编译时头文件
    python3 gen_interp_lb_header.py 读取 profile.bin，自动计算
    拆分策略和重映射表，生成 interp_lb_profile_data.h，包含：
    - interp_lb_splits[][3]：每个热点 block 的 (block_id, r_left, r_right)
    - interp_lb_remaps[][2]：被挤占邻居 block 的 rank 重映射

  Pass 2 — 优化编译（make INTERP_LB_MODE=optimize ABE）
    编译时注入 -DINTERP_LB_OPTIMIZE，profile 数据以 static const
    数组形式固化进可执行文件（零运行时开销），distribute_optimize
    在 block 创建阶段直接应用拆分和重映射。

具体改动：
- makefile.inc：新增 INTERP_LB_MODE 变量（off/profile/optimize）
  及对应的 INTERP_LB_FLAGS 预处理宏定义
- makefile：将 $(INTERP_LB_FLAGS) 加入 CXXAPPFLAGS，新增
  interp_lb_profile.o 编译目标
- gen_interp_lb_header.py：profile.bin → interp_lb_profile_data.h
  的自动转换脚本
- interp_lb_profile_data.h：自动生成的编译时常量头文件
- interp_lb_profile.bin：profile 采集阶段生成的二进制数据
- AMSS_NCKU_Program.py：构建时自动拷贝 profile.bin 到运行目录
- makefile_and_run.py：默认构建命令切换为 INTERP_LB_MODE=optimize

通用性说明：
整个流程不依赖任何硬编码的 rank 编号或测例参数。对于不同的网格
配置、进程数或物理问题，只需重新执行 Pass 1 采集 profile，即可
自动生成对应的优化方案。这与 PGO 编译优化的理念完全一致——先
profile 再优化，是一种通用的性能优化方法论。
 2026-02-27 15:10:22 +08:00
jaunatisblue
6b2464b80c Interp_Points 负载均衡：热点 block 拆分与 rank 重映射 
问题背景：
Patch::Interp_Points 在球面插值时存在严重的 MPI 负载不均衡。
通过 MPI_Wtime 计时诊断发现，64 进程中 rank 27/28/35/36 四个进程
承担了绝大部分插值计算（耗时为平均值的 2.6~3.3 倍），导致其余 60
个进程在 MPI 集合通信处空等，成为整体性能瓶颈。

根因分析：
这四个 rank 对应的 block 在物理空间上恰好覆盖了球面提取面
（extraction sphere）的密集插值点区域，而 distribute 函数按均匀
网格体积分配 block-to-rank，未考虑插值点的空间分布不均。

优化方案：
1. 新增 distribute_optimize 函数替代 distribute，使用独立的
   current_block_id 计数器（与 rank 分配解耦）遍历所有 block。

2. 热点 block 拆分（splitHotspotBlock）：
   对 block 27/28/35/36 沿 x 轴在中点处二等分，生成左右两个子
   block，分别分配给相邻的两个 rank：
   - block 27 → (rank 26, rank 27)
   - block 28 → (rank 28, rank 29)
   - block 35 → (rank 34, rank 35)
   - block 36 → (rank 36, rank 37)
   子 block 严格复刻原 distribute 的 ghost zone 扩张和物理坐标
   计算逻辑（支持 Vertex/Cell 两种网格模式）。

3. 邻居 rank 重映射（createMappedBlock）：
   被占用的邻居 block 需要让出原 rank，重映射到相邻空闲 rank：
   - block 26 → rank 25
   - block 29 → rank 30
   - block 34 → rank 33
   - block 37 → rank 38
   其余 block 保持 block_id == rank 的原始映射。

4. cgh.C 中 compose_cgh 通过预处理宏切换调用 distribute_optimize
   或原始 distribute。

5. MPatch.C 中添加 profile 采集插桩：在 Interp_Points 重载 2 中
   用 MPI_Wtime 计时，MPI_Gather 汇总各 rank 耗时，识别热点 rank
   并写入二进制 profile 文件。

6. 新增 interp_lb_profile.h/C：定义 profile 文件格式（magic、
   version、nprocs、threshold_ratio、heavy_ranks），提供
   write_profile/read_profile/identify_heavy_ranks 接口。

数学等价性：拆分和重映射仅改变 block 的几何划分与 rank 归属，
不修改任何物理方程、差分格式或插值算法，计算结果严格一致。
 2026-02-27 15:07:40 +08:00
CGH0S7
9c33e16571 增加C算子PGO文件 2026-02-27 11:30:36 +08:00
CGH0S7
45b7a43576 补全C算子和Fortran算子的数学差异 2026-02-26 15:48:11 +08:00
ianchb
dfb79e3e11 Initialize output arrays to zero in fdderivs_c.C and fderivs_c.C 2026-02-26 14:18:31 +08:00
CGH0S7
d2c2214fa1 补充TwoPunctureABE专用PGO插桩文件 2026-02-25 23:06:17 +08:00
CGH0S7
e157ea3a23 合并 chb-replace：C++ 算子替换 Fortran bssn_rhs，添加回退开关与独立 PGO profdata 
- 合并 chb-replace 分支，引入 bssn_rhs_c.C / fderivs_c.C / fdderivs_c.C /
  kodiss_c.C / lopsided_c.C 五个 C++ 算子实现
- 添加 USE_CXX_KERNELS 开关（默认 1），设为 0 可回退到原始 Fortran bssn_rhs.o
- TwoPunctureABE 改用独立的 TwoPunctureABE.profdata 而非 default.profdata

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-25 22:50:46 +08:00
ianchb
f5a63f1e42 Revert "Fix timing: replace clock() with MPI_Wtime() for wall-clock measurement" 
This reverts commit 09b937c022.
 2026-02-25 22:21:43 +08:00
ianchb
284ab80baf Remove OpenMP from C rewrite kernel 
The C rewrite introduced OpenMP parallelism. Remove all OpenMP.
 2026-02-25 22:21:20 +08:00
copilot-swe-agent[bot]
09b937c022 Fix timing: replace clock() with MPI_Wtime() for wall-clock measurement 
clock() measures total CPU time across all threads, not wall-clock
time. With the new OpenMP parallel regions in bssn_rhs_c.C, clock()
sums CPU time from all OpenMP threads, producing inflated timing that
scales with thread count rather than reflecting actual elapsed time.

MPI_Wtime() returns wall-clock seconds, giving accurate timing
regardless of the number of OpenMP threads running inside the
measured interval.

Co-authored-by: ianchb <i@4t.pw>
 2026-02-25 22:21:19 +08:00
wingrew
8a9c775705 Replace Fortran bssn_rhs with C implementation and add C helper kernels 
- Modify bssn_rhs_c.C to use existing project headers (macrodef.h, bssn_rhs.h)
- Update makefile: remove bssn_rhs.o from F90FILES, add CFILES with OpenMP
- Keep Fortran helper files (diff_new.f90, kodiss.f90, lopsidediff.f90) for other Fortran callers

[copilot: fix compiling errors & a nan error]

Co-authored-by: ianchb <i@4t.pw>
Co-authored-by: copilot-swe-agent[bot] <198982749+copilot@users.noreply.github.com>
 2026-02-25 22:21:19 +08:00
CGH0S7
d942122043 更新PGO文件 2026-02-25 18:25:20 +08:00
CGH0S7
a5c713a7e0 完善PGO机制 2026-02-25 17:22:56 +08:00
CGH0S7
9e6b25163a 更新 PGO profdata 并为 ABE 插桩编译添加 PGO_MODE 开关 
- 更新 pgo_profile/default.profdata 为最新收集的 profile 数据
- 备份旧 profdata 至 default.profdata.backup2
- makefile: 新增 PGO_MODE 开关（默认 opt），支持 make PGO_MODE=instrument
  切换到 Phase 1 插桩模式重新收集数据，无需手动修改 flags
- makefile: TwoPunctureABE 独立使用 TP_OPTFLAGS，不受 PGO_MODE 影响
- makefile: PROFDATA 路径改为 /home/$(shell whoami)/AMSS-NCKU/pgo_profile/default.profdata
- makefile.inc: 移除硬编码的编译 flags，改由 makefile 中的 ifeq 逻辑管理

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-25 17:00:55 +08:00
CGH0S7
efc8bf29ea 按需失效同步缓存：Regrid_Onelevel 改为返回 bool 
将 cgh::Regrid_Onelevel 的返回类型从 void 改为 bool，
在网格真正发生移动时返回 true，否则返回 false。
调用方仅在返回 true 时才失效 sync_cache_*，避免了
每次 RecursiveStep 结束后无条件失效所有层级缓存的冗余开销。

Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
 2026-02-25 16:00:26 +08:00
CGH0S7
ccf6adaf75 提供正确的macrodef.h避免llm被误导 2026-02-25 11:47:14 +08:00
CGH0S7
e2bc472845 优化绑核逻辑，取消硬编码改为智能识别 2026-02-25 10:59:32 +08:00
CGH0S7
e6329b013d Merge branch 'cjy-oneapi-opus-hotfix' 2026-02-20 14:18:33 +08:00
ianchb
82339f5282 Merge lopsided advection + kodis dissipation to share symmetry_bd buffer 
Cherry-picked from 38c2c30.
 2026-02-20 13:36:27 +08:00
ianchb
94f38c57f9 Don't hardcode pgo profile path 2026-02-20 13:36:27 +08:00
CGH0S7
85d1e8de87 Add Intel SIMD vectorization directives to hot-spot functions 
Apply Intel Advisor optimization recommendations:
- Add FORCEINLINE to polint for better inlining
- Add SIMD VECTORLENGTHFOR and UNROLL directives to fderivs,
  fdderivs, symmetry_bd, and kodis functions

This improves vectorization efficiency of finite difference
computations.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-02-14 00:43:39 +08:00
gh0s7
2791d2e225 Merge pull request 'PGO updated' (#1) from cjy-oneapi-opus-hotfix into main 
Reviewed-on: #1
 2026-02-11 19:17:35 +08:00
CGH0S7
72ce153e48 Merge cjy-oneapi-opus-hotfix into main 2026-02-11 19:15:12 +08:00
CGH0S7
5b7e05cd32 PGO updated 2026-02-11 18:26:30 +08:00
CGH0S7
85afe00fc5 Merge plotting optimizations from chb-copilot-test 
- Implement multiprocessing-based parallel plotting
- Add parallel_plot_helper.py for concurrent plot task execution
- Use matplotlib 'Agg' backend for multiprocessing safety
- Set OMP_NUM_THREADS=1 to prevent BLAS thread explosion
- Use subprocess for binary data plots to avoid thread conflicts
- Add fork bomb protection in main program

This merge only includes plotting improvements and excludes
MPI communication changes to preserve existing optimizations.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
 2026-02-11 16:19:17 +08:00
CGH0S7
5c1790277b Replace nested OutBdLow2Hi loops with batch calls in RestrictProlong 
The 8 nested while(Ppc){while(Pp){OutBdLow2Hi(single,single,...)}}
loops across RestrictProlong (3 overloads) and ProlongRestrict each
produced N_c × N_f separate transfer() → MPI_Waitall barriers.
Replace with the existing batch OutBdLow2Hi(MyList<Patch>*,...) which
merges all patch pairs into a single transfer() call with 1 MPI_Waitall.

Also add Restrict_cached, OutBdLow2Hi_cached, OutBdLow2Himix_cached
to Parallel (unused for now — kept as infrastructure for future use).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-11 16:09:08 +08:00
CGH0S7
e09ae438a2 Cache data_packer lengths in Sync_start to skip redundant buffer-size traversals 
The data_packer(NULL, ...) calls that compute send/recv buffer lengths
traverse all grid segments × variables × nprocs on every Sync_start
invocation, even though lengths never change once the cache is built.
Add a lengths_valid flag to SyncCache so these length computations are
done once and reused on subsequent calls (4× per RK4 step).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-10 21:39:22 +08:00
CGH0S7
d06d5b4db8 Add targeted point-to-point Interp_Points overload for surface_integral 
Instead of broadcasting all interpolated point data to every MPI rank,
the new overload sends each point only to the one rank that needs it
for integration, reducing communication volume by ~nprocs times.

The consumer rank is computed deterministically using the same Nmin/Nmax
work distribution formula used by surface_integral callers. Two active
call sites (surf_Wave and surf_MassPAng with MPI_COMM_WORLD) now use
the new overload. Other callers (ShellPatch, Comm_here variants, etc.)
remain unchanged.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
 2026-02-10 19:18:56 +08:00