chore(avm): improve column stats (#11135)

Now that we use tight polynomials it makes sense to count things differently for our stats. I'm gathering info in particular to see if it makes sense to use `commit_sparse` (which we _are_ using now). From what I can see, probably not, or we should do it dynamically based on sparseness information. Stats from the bulk test. ``` Median column fullness: 90% Average column fullness: 66% Fullness of all columns, ignoring empty ones: 1: 100% 705: 100% 695: 100% 691: 100% 690: 100% 689: 100% 688: 100% 657: 100% 649: 100% 638: 100% 637: 100% 636: 100% 632: 100% 268: 100% 267: 100% 194: 100% 0: 100% 25: 100% 15: 100% 20: 100% 11: 100% 8: 100% 2: 100% 66: 99% 175: 99% 75: 99% 90: 99% 101: 99% 108: 99% 117: 99% 136: 99% 149: 99% 150: 99% 153: 99% 156: 99% 157: 99% 158: 99% 176: 99% 177: 99% 178: 99% 186: 99% 3: 99% 196: 99% 308: 99% 307: 99% 302: 99% 282: 99% 275: 99% 274: 99% 35: 99% 631: 99% 650: 99% 12: 99% 48: 99% 4: 99% 644: 98% 276: 98% 273: 98% 6: 96% 672: 96% 666: 96% 673: 96% 658: 95% 120: 94% 139: 92% 141: 92% 143: 92% 140: 92% 144: 92% 121: 92% 674: 91% 43: 91% 682: 91% 46: 91% 678: 91% 677: 91% 675: 91% 472: 90% 471: 90% 454: 90% 445: 90% 470: 90% 455: 90% 456: 90% 457: 90% 458: 90% 459: 90% 469: 90% 468: 90% 460: 90% 461: 90% 467: 90% 466: 90% 465: 90% 462: 90% 463: 90% 464: 90% 485: 90% 497: 90% 496: 90% 495: 90% 494: 90% 493: 90% 492: 90% 491: 90% 490: 90% 489: 90% 488: 90% 487: 90% 486: 90% 473: 90% 484: 90% 483: 90% 482: 90% 481: 90% 480: 90% 479: 90% 478: 90% 477: 90% 476: 90% 475: 90% 474: 90% 401: 90% 426: 90% 425: 90% 424: 90% 423: 90% 422: 90% 421: 90% 400: 90% 420: 90% 419: 90% 418: 90% 417: 90% 416: 90% 415: 90% 427: 90% 402: 90% 403: 90% 414: 90% 404: 90% 405: 90% 413: 90% 412: 90% 411: 90% 410: 90% 409: 90% 408: 90% 406: 90% 439: 90% 452: 90% 451: 90% 450: 90% 449: 90% 448: 90% 447: 90% 446: 90% 407: 90% 444: 90% 443: 90% 442: 90% 441: 90% 440: 90% 453: 90% 438: 90% 437: 90% 398: 90% 436: 90% 435: 90% 434: 90% 433: 90% 432: 90% 431: 90% 430: 90% 429: 90% 428: 90% 565: 90% 578: 90% 577: 90% 576: 90% 575: 90% 574: 90% 573: 90% 572: 90% 571: 90% 570: 90% 569: 90% 568: 90% 567: 90% 566: 90% 579: 90% 564: 90% 563: 90% 562: 90% 561: 90% 560: 90% 559: 90% 558: 90% 557: 90% 556: 90% 555: 90% 554: 90% 553: 90% 593: 90% 629: 90% 627: 90% 626: 90% 625: 90% 624: 90% 623: 90% 622: 90% 621: 90% 620: 90% 619: 90% 618: 90% 617: 90% 594: 90% 552: 90% 592: 90% 591: 90% 590: 90% 589: 90% 587: 90% 586: 90% 585: 90% 584: 90% 583: 90% 582: 90% 581: 90% 580: 90% 511: 90% 524: 90% 523: 90% 522: 90% 521: 90% 520: 90% 519: 90% 518: 90% 517: 90% 516: 90% 515: 90% 514: 90% 513: 90% 512: 90% 525: 90% 510: 90% 509: 90% 508: 90% 507: 90% 506: 90% 505: 90% 504: 90% 503: 90% 502: 90% 501: 90% 500: 90% 499: 90% 538: 90% 551: 90% 550: 90% 549: 90% 548: 90% 547: 90% 546: 90% 545: 90% 544: 90% 543: 90% 542: 90% 541: 90% 540: 90% 539: 90% 498: 90% 537: 90% 536: 90% 535: 90% 534: 90% 533: 90% 532: 90% 531: 90% 530: 90% 529: 90% 528: 90% 527: 90% 526: 90% 352: 90% 343: 90% 344: 90% 345: 90% 346: 90% 347: 90% 348: 90% 349: 90% 350: 90% 351: 90% 342: 90% 353: 90% 354: 90% 355: 90% 356: 90% 357: 90% 358: 90% 359: 90% 360: 90% 333: 90% 399: 90% 326: 90% 327: 90% 328: 90% 329: 90% 330: 90% 331: 90% 332: 90% 397: 90% 334: 90% 335: 90% 336: 90% 337: 90% 338: 90% 339: 90% 340: 90% 341: 90% 388: 90% 380: 90% 381: 90% 382: 90% 383: 90% 384: 90% 385: 90% 386: 90% 387: 90% 362: 90% 389: 90% 390: 90% 391: 90% 392: 90% 393: 90% 394: 90% 395: 90% 396: 90% 378: 90% 379: 90% 361: 90% 363: 90% 364: 90% 365: 90% 366: 90% 367: 90% 368: 90% 369: 90% 370: 90% 371: 90% 372: 90% 373: 90% 374: 90% 375: 90% 376: 90% 377: 90% 44: 89% 312: 88% 305: 88% 31: 87% 72: 86% 676: 86% 45: 85% 280: 84% 311: 84% 91: 83% 163: 80% 185: 80% 272: 78% 190: 74% 199: 74% 182: 73% 187: 70% 132: 70% 125: 70% 5: 66% 197: 65% 180: 63% 119: 63% 165: 60% 700: 60% 135: 57% 62: 56% 63: 53% 64: 53% 49: 51% 671: 50% 670: 50% 668: 50% 667: 50% 680: 50% 18: 50% 145: 50% 146: 50% 148: 50% 174: 47% 701: 44% 287: 39% 281: 39% 41: 37% 588: 36% 192: 36% 164: 35% 198: 34% 285: 34% 181: 34% 37: 34% 38: 34% 151: 33% 651: 33% 652: 33% 642: 32% 653: 32% 654: 32% 635: 32% 655: 32% 656: 32% 122: 29% 201: 28% 236: 28% 39: 26% 67: 25% 40: 21% 203: 18% 123: 18% 286: 18% 53: 17% 10: 16% 283: 15% 200: 13% 173: 13% 230: 13% 702: 13% 183: 13% 683: 11% 696: 11% 52: 10% 248: 9% 166: 9% 42: 8% 54: 8% 697: 8% 7: 7% 685: 7% 229: 7% 288: 7% 234: 6% 270: 5% 55: 4% 235: 3% 278: 3% 33: 3% 71: 3% 56: 3% 167: 3% 693: 3% 218: 3% 50: 3% 28: 2% 227: 2% 226: 2% 304: 1% 74: 1% 59: 1% 9: 1% 155: 1% 643: 1% 30: 1% 208: 1% 646: 1% 665: 1% 238: 1% 239: 1% 692: 0% 27: 0% 687: 0% 58: 0% 686: 0% 57: 0% 684: 0% 704: 0% 660: 0% 659: 0% 47: 0% 703: 0% 51: 0% 694: 0% 258: 0% 241: 0% 243: 0% 244: 0% 245: 0% 246: 0% 247: 0% 249: 0% 250: 0% 251: 0% 252: 0% 253: 0% 254: 0% 255: 0% 256: 0% 257: 0% 240: 0% 261: 0% 269: 0% 277: 0% 289: 0% 290: 0% 291: 0% 292: 0% 293: 0% 294: 0% 295: 0% 296: 0% 297: 0% 303: 0% 309: 0% 212: 0% 68: 0% 73: 0% 152: 0% 160: 0% 161: 0% 162: 0% 188: 0% 189: 0% 195: 0% 204: 0% 206: 0% 207: 0% 209: 0% 210: 0% 211: 0% 65: 0% 214: 0% 215: 0% 216: 0% 217: 0% 219: 0% 220: 0% 222: 0% 223: 0% 224: 0% 225: 0% 231: 0% 232: 0% 233: 0% 237: 0% Details for 20 most sparse columns: Column main_sel_op_msm: 2 non-zero entries out of 28048 (0%) Column main_sel_op_l2gasleft: 1 non-zero entries out of 28904 (0%) Column main_sel_op_l1_to_l2_msg_exists: 1 non-zero entries out of 35497 (0%) Column main_sel_op_keccak: 1 non-zero entries out of 14710 (0%) Column main_sel_op_get_contract_instance: 3 non-zero entries out of 28157 (0%) Column main_sel_op_fee_per_l2_gas: 1 non-zero entries out of 28740 (0%) Column main_sel_op_fee_per_da_gas: 1 non-zero entries out of 28825 (0%) Column main_sel_op_fdiv: 40 non-zero entries out of 27798 (0%) Column main_sel_op_external_return: 3 non-zero entries out of 36569 (0%) Column main_sel_op_external_call: 1 non-zero entries out of 35820 (0%) Column main_sel_op_emit_unencrypted_log: 3 non-zero entries out of 35147 (0%) Column main_sel_op_emit_nullifier: 1 non-zero entries out of 35335 (0%) Column main_sel_op_emit_note_hash: 1 non-zero entries out of 35291 (0%) Column main_sel_op_emit_l2_to_l1_msg: 1 non-zero entries out of 35580 (0%) Column alu_remainder: 6 non-zero entries out of 6708 (0%) Column main_sel_op_debug_log: 31 non-zero entries out of 36202 (0%) Column main_sel_op_dagasleft: 1 non-zero entries out of 28983 (0%) Column main_sel_op_chain_id: 1 non-zero entries out of 28426 (0%) Column main_sel_op_calldata_copy: 6 non-zero entries out of 36361 (0%) Column main_sel_op_block_number: 1 non-zero entries out of 28580 (0%) ```
AztecProtocol · Jan 9, 2025 · 535a14c · 535a14c
1 parent 61c3e95
commit 535a14c
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diff --git a/barretenberg/cpp/src/barretenberg/vm/avm/generated/full_row.hpp b/barretenberg/cpp/src/barretenberg/vm/avm/generated/full_row.hpp
@@ -29,7 +29,7 @@ template <typename FF_> struct AvmFullRow {
     const FF& get_column(ColumnAndShifts col) const
     {
         static_assert(sizeof(*this) == sizeof(FF) * static_cast<size_t>(ColumnAndShifts::NUM_COLUMNS));
-        return reinterpret_cast<FF*>(this)[static_cast<size_t>(col)];
+        return reinterpret_cast<const FF*>(this)[static_cast<size_t>(col)];
     }
 };
 

diff --git a/barretenberg/cpp/src/barretenberg/vm/avm/trace/execution.cpp b/barretenberg/cpp/src/barretenberg/vm/avm/trace/execution.cpp
@@ -1,11 +1,14 @@
 #include "barretenberg/vm/avm/trace/execution.hpp"
 #include "barretenberg/bb/log.hpp"
 #include "barretenberg/common/serialize.hpp"
+#include "barretenberg/common/thread.hpp"
 #include "barretenberg/common/throw_or_abort.hpp"
 #include "barretenberg/numeric/uint256/uint256.hpp"
 #include "barretenberg/vm/avm/generated/circuit_builder.hpp"
+#include "barretenberg/vm/avm/generated/columns.hpp"
 #include "barretenberg/vm/avm/generated/composer.hpp"
 #include "barretenberg/vm/avm/generated/flavor.hpp"
+#include "barretenberg/vm/avm/generated/full_row.hpp"
 #include "barretenberg/vm/avm/generated/verifier.hpp"
 #include "barretenberg/vm/avm/trace/common.hpp"
 #include "barretenberg/vm/avm/trace/deserialization.hpp"
@@ -139,44 +142,79 @@ void show_trace_info(const auto& trace)
         return;
     }
 
-    const size_t total_elements = trace.front().SIZE * trace.size();
-    const size_t nonzero_elements = [&]() {
-        size_t count = 0;
-        for (auto const& row : trace) {
-            for (const auto& ff : row.as_vector()) {
-                if (!ff.is_zero()) {
-                    count++;
-                }
+    // Calculate number of non-zero entries in each column.
+    struct ColumnStats {
+        size_t column_number = 0;
+        size_t non_zero_entries = 0;
+        size_t total_entries = 0;
+        size_t fullness = 0; // 0 to 100.
+    };
+    std::vector<ColumnStats> column_stats(static_cast<size_t>(avm::ColumnAndShifts::NUM_COLUMNS));
+    bb::parallel_for(static_cast<size_t>(avm::ColumnAndShifts::NUM_COLUMNS), [&](size_t col) {
+        size_t non_zero_entries = 0;
+        ssize_t last_non_zero_row = -1;
+        for (uint32_t row_n = 0; row_n < trace.size(); row_n++) {
+            const auto& row = trace.at(row_n);
+            if (!row.get_column(static_cast<avm::ColumnAndShifts>(col)).is_zero()) {
+                non_zero_entries++;
+                last_non_zero_row = row_n;
             }
         }
-        return count;
-    }();
-    vinfo("Number of non-zero elements: ",
-          nonzero_elements,
-          "/",
-          total_elements,
-          " (",
-          100 * nonzero_elements / total_elements,
-          "%)");
-    const size_t non_zero_columns = [&]() {
-        std::vector<bool> column_is_nonzero(trace.front().SIZE, false);
-        for (auto const& row : trace) {
-            const auto row_vec = row.as_vector();
-            for (size_t col = 0; col < row.SIZE; col++) {
-                if (!row_vec[col].is_zero()) {
-                    column_is_nonzero[col] = true;
-                }
+        size_t size = static_cast<size_t>(last_non_zero_row + 1);
+        column_stats[col] = { .column_number = col,
+                              .non_zero_entries = non_zero_entries,
+                              .total_entries = size,
+                              .fullness = size > 0 ? non_zero_entries * 100 / size : 0 };
+    });
+    // ignore empty columns because they don't cost anything.
+    std::erase_if(column_stats, [](const ColumnStats& stat) { return stat.total_entries == 0; });
+    std::sort(column_stats.begin(), column_stats.end(), [](const ColumnStats& a, const ColumnStats& b) {
+        return a.fullness > b.fullness;
+    });
+    vinfo(
+        "Median column fullness: ",
+        [&]() {
+            const auto& median_stat = column_stats.at(column_stats.size() / 2);
+            return median_stat.fullness;
+        }(),
+        "%");
+    vinfo(
+        "Average column fullness: ",
+        [&]() {
+            size_t fullness_sum = 0;
+            for (const auto& stat : column_stats) {
+                fullness_sum += stat.fullness;
             }
+            return static_cast<int>(fullness_sum / column_stats.size());
+        }(),
+        "%");
+    if (getenv("AVM_FULL_COLUMN_STATS") != nullptr) {
+        vinfo("Fullness of all columns, ignoring empty ones:");
+        // Print fullness of all columns in descending order and batches of 10.
+        for (size_t i = 0; i < column_stats.size(); i += 10) {
+            std::string fullnesses;
+            for (size_t j = i; j < i + 10 && j < column_stats.size(); j++) {
+                const auto& stat = column_stats.at(j);
+                fullnesses += std::format("{:3}: {:3}%  ", stat.column_number, stat.fullness);
+            }
+            vinfo(fullnesses);
+        }
+
+        vinfo("Details for 20 most sparse columns:");
+        const auto names = AvmFullRow<FF>::names();
+        for (size_t i = 0; i < 20; i++) {
+            const auto& stat = column_stats.at(column_stats.size() - i - 1);
+            vinfo("Column \"",
+                  names.at(stat.column_number),
+                  "\": ",
+                  stat.non_zero_entries,
+                  " non-zero entries out of ",
+                  stat.total_entries,
+                  " (",
+                  stat.fullness,
+                  "%)");
         }
-        return static_cast<size_t>(std::count(column_is_nonzero.begin(), column_is_nonzero.end(), true));
-    }();
-    vinfo("Number of non-zero columns: ",
-          non_zero_columns,
-          "/",
-          trace.front().SIZE,
-          " (",
-          100 * non_zero_columns / trace.front().SIZE,
-          "%)");
+    }
 }
 
 } // namespace

diff --git a/bb-pilcom/bb-pil-backend/templates/full_row.hpp.hbs b/bb-pilcom/bb-pil-backend/templates/full_row.hpp.hbs
@@ -30,7 +30,7 @@ struct AvmFullRow {
     const FF& get_column(ColumnAndShifts col) const
     {
         static_assert(sizeof(*this) == sizeof(FF) * static_cast<size_t>(ColumnAndShifts::NUM_COLUMNS));
-        return reinterpret_cast<FF*>(this)[static_cast<size_t>(col)];
+        return reinterpret_cast<const FF*>(this)[static_cast<size_t>(col)];
     }
 };