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"XRP: In-Kernel Storage Functions with eBPF. OSDI 2022." 값의 "Evidence overview" 속성을 가진 모든 문서의 목록입니다. 결과가 얼마 안 되기 때문에 주변의 값을 표시합니다.

1번 부터의 결과 26개입니다.

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결과 목록

  • Lesson:ugache a unified gpu cache for embedding based deep learning 227e7c8f  + (Xiaoniu Song et al., "UGACHE: A Unified GPU Cache for Embedding-based Deep Learning", SOSP 2023. Source: https://sigops.org/s/conferences/sosp/2023/toc.html Verification basis: official_abstract. Canonical evidence ID: canonical-paper-v2-227e7c8f)
  • Lesson:sieve is simpler than lru an efficient turn key eviction algorithm for web caches 86f86293  + (Yazhuo Zhang et al., "SIEVE is Simpler tha … Yazhuo Zhang et al., "SIEVE is Simpler than LRU: an Efficient Turn-Key Eviction Algorithm for Web Caches", NSDI 2024.</br>Source: https://www.pdl.cmu.edu/ftp/Storage/nsdi24-SIEVE_abs.shtml</br>Verification basis: official_abstract.</br>Canonical evidence ID: canonical-paper-v2-86f86293l evidence ID: canonical-paper-v2-86f86293)
  • Lesson:rearchitecting buffered i o in the era of high bandwidth ssd 70b23de3  + (Yekang Zhan; Tianze Wang; Zheng Peng; Haic … Yekang Zhan; Tianze Wang; Zheng Peng; Haichuan Hu; Jiahao Wu; Xiangrui Yang; Qiang Cao; Hong Jiang; Jie Yao. Rearchitecting Buffered I/O in the Era of High-Bandwidth SSDs. FAST, 2026.</br>Source: https://www.usenix.org/conference/fast26/presentation/zhan</br>Verification basis: official_abstract.</br>Canonical evidence ID: canonical-paper-v2-70b23de3l evidence ID: canonical-paper-v2-70b23de3)
  • Lesson:accl an fpga based collective engine for distributed applications 896d30fd  + (Zhenhao He et al., "ACCL+: an FPGA-Based Collective Engine for Distributed Applications", OSDI 2024. Source: https://arxiv.org/abs/2312.11742 Verification basis: official_abstract. Canonical evidence ID: canonical-paper-v2-896d30fd)
  • Lesson:pivot-b200-20260717-zmq-ipc-path-a01  + (a02 decision SHA-256 b8a1ebaed3c48842cd10768235d66ff1985c2cc8d9c20bdfd046ae4db72996f4; Qwen log SHA-256 85237dd99be24c2c20386d96ab756d463b64540eb282bfc45629716b698992fc; no GPU compute process.)
  • Lesson:compare identical source envelopes at long run boundaries 5f58511d  + (a03 decision and model artifact hashes; implementation fix commit 99ccfb7b7; full scripts suite 285 passed; pre-commit passed.)
  • Lesson:separate semantic replication hashes from provenance bound artifact hashes e7ab7a4e  + (a04 decision SHA-256 3627583ec41aa159b7aa0 … a04 decision SHA-256 3627583ec41aa159b7aa08818b0140d82e1296a59774cf9f61acf77e78a9a97e; a04 Qwen b7e0e9eab21f27f9f5e2e65d25b5e49ec839bc5037aae44d59ffbd3391e57945; a04 Mistral 343e703110e98a2d13b41152a01daec6dbc489ab950727ab1c550fc21ee5a1a6; full validator passed with verify_files and verify_commit.assed with verify_files and verify_commit.)
  • Lesson:research autopilot 20260723t090001z-gpu  + (algebraic-ml-compiler/RESEARCH/precision_a … algebraic-ml-compiler/RESEARCH/precision_aware_rewrite_legality_20260718_174112/theorem_v3_cuda_sm89_validation_20260722.json; algebraic-ml-compiler/RESEARCH/precision_aware_rewrite_legality_20260718_174112/pretrained_kv_cache_quality_l40s_20260722.json; .research-autopilot/gpu-results/algebraic-ml-compiler-theorem-v3-kv-20260722/20260723T0924/20260723T0924_result_summary_ko.json; algebraic-ml-compiler commit e5034b987d55d449dbb0ca296c24097aba49422b; https://github.com/mrcha033/algebraic-ml-compiler/pull/1.com/mrcha033/algebraic-ml-compiler/pull/1)
  • Lesson:dwkv kv saturation unproven  + (archive warning, pre-pivot simulation caveats, legacy diagnostics and telemetry notes)
  • Lesson:dwkv metric mismatch  + (corrected-design policy table and metric caveat in archived SOTA findings)
  • Lesson:dlora dynamically orchestrating requests and adapters for lora llm serving 3827bfa3  + (dLoRA: Dynamically Orchestrating Requests and Adapters for LoRA LLM Serving. OSDI 2024.)
  • Lesson:research autopilot 20260723t030001z  + (docs/evidence/diversifier_track_ablation_t … docs/evidence/diversifier_track_ablation_transfer_v3.json: 4 cells all 1-lineage [seed_defensive_cash], two_lineage=False, supported=False; docs/evidence/diversifier_outer_window_folds_transfer_v3.json: 3 folds dSharpe=0.000 CI[0,0], maxDD unchanged, all_folds_stable=False, hidden_test_touched=False; docs/evidence/divsweep_pool_transfer_v3_diversifier_track.json: n_admitted=0; seed_crisis_hedge fitness -0.053 < floor 0.0; seed_equal_risk mean\\|corr\\| 0.520 > 0.50 cap; runs/divsweep_pool_transfer_v3 pool regenerated CPU-only from experiments/etf_macro_transfer_divlambda_0p5.yaml (max_generations=0, no LLM); alpha verify-data passes; full pytest 376 passed / 2 pre-existing fixture failures; alpha-factory commit 5d8056d20c493207215a9d679f492dc81588c598; https://github.com/mrcha033/alpha-factory/pull/1om/mrcha033/alpha-factory/pull/1)
  • Lesson:research autopilot 20260721t090001z  + (docs/evidence/divsweep_pool_v3_leaderboard … docs/evidence/divsweep_pool_v3_leaderboard.csv (v3 pool, 3 gate-passers unchanged from v2); docs/evidence/diversifier_track_ablation_v3.json (2x2: only (on,0.5) is 2-lineage, Sharpe 1.6218, maxDD -2.57%); docs/evidence/diversifier_selection_sensitivity_v3.json (Sharpe delta +0.314 CI95 [+0.029,+0.62], P(delta<=0)=1.3%, CSCV PBO=0.000); docs/evidence/divsweep_pool_v3_diversifier_track.json (seed_crisis_hedge admitted, fit 0.50, mean\\|corr\\| 0.27); pytest 371 passed / 2 known fixture-missing; alpha-factory commit f8e17cd2a2c1705365044fb3c5866fffc3d03030; https://github.com/mrcha033/alpha-factory/pull/1hub.com/mrcha033/alpha-factory/pull/1)
  • Lesson:research autopilot 20260721t210001z  + (experiments/diversifier_outer_window_folds … experiments/diversifier_outer_window_folds.py replayed on divsweep_pool_v3; deterministic (seed 20260721), reproduces docs/evidence/diversifier_outer_window_folds_v3.json byte-for-byte; Per-fold: fold_1 dSharpe +0.123 CI[-0.94,+0.96] P(d<=0)=0.443; fold_2 +0.040 CI[-0.35,+0.46] 0.429; fold_3 +0.313 CI[+0.03,+0.62] 0.013; pooled(1760 obs) +0.046 CI[-0.27,+0.38] 0.391; all_folds_stable=True (2 lineages, Sharpe non-inferior, DD improved every fold); admission decision window-independent by construction (corr-to-elite over full research prefix); tests/test_diversifier_outer_window_design.py 5 passed; full suite 376 passed / 2 pre-existing fixture-missing failures; Hidden suffix [0.94,1.0] never touched; oracle reproduces builder validate Sharpe within 0.02 per fold; alpha-factory commit fc5de9cb146144570971c1f53094cb73603b942b; https://github.com/mrcha033/alpha-factory/pull/1ull/1)
  • Lesson:research autopilot 20260722t090001z  + (experiments/predict_working_set_knee.py (r … experiments/predict_working_set_knee.py (run_stability, --repeats) and committed receipt experiments/results/working_set_knee_cpu.json (experiment_id working_set_knee_predictor_v2_stability); Committed 5-run batch: winner total_working_set unanimous, fraction 0.662±0.035, single-run CV 0.072-0.312, LOO max 14-71%, output-share corr −0.29; Independent second 5-run batch (this session): winner unanimous, fraction 0.597±0.013, single-run CV 0.067-0.223, LOO max 14.1-43.4%, output-share corr −0.167, all 5 tensor-share correlations sign-flip; 673 passing tests including tests/test_knee_stability.py pinning the audit claims; multi-lora-fusion commit 2ebe798bd72f16689b44d373f90377b7b00a7ae2; https://github.com/mrcha033/multi-lora-fusion/pull/1thub.com/mrcha033/multi-lora-fusion/pull/1)
  • Lesson:research autopilot 20260721t030001z  + (experiments/results/spill_resolving_power_ … experiments/results/spill_resolving_power_v1.json: one reload-law-identifying family (rect-k32-j128), counter_divergence_ratio=4.0, timing_divergence_pp=39.33, primary_falsifiable_if_challenger_true=true; other three families divergence 0pp; src/spill_validation_contract.py resolving_power() and score_reload_law(); frozen predictions give linear-K spill-load 23.6/46.0 kB vs constant 94.3/184.1 kB per problem at rect-k32-j128; 1,232 tests pass including selection of the true reload law from the local-load counter under validated fixtures; preflight receipt byte-identical and contract_sha256 unchanged; mlir-fft-compiler commit a0a464ea5a5f4f353574da7cd632cb6fcf5241fa; https://github.com/mrcha033/mlir-fft-compiler/pull/1thub.com/mrcha033/mlir-fft-compiler/pull/1)
  • Lesson:pivot-b200-20260717-launch-lock-a01  + (failed pre-GPU tmux attempt at source commit 01031e6e484bbd98e00bdc3320f77c45d292f6e1; fixed by commit 8ca2dbb68 adding exact .gitignore entries; no artifact or performance data produced)
  • Lesson:research autopilot 20260726t090001z  + (leave_one_shape_out on results/l40s_gpu3_b … leave_one_shape_out on results/l40s_gpu3_bsr_dispatch.json (63 pts, 3 folds): parametric +2.6%/fs=0, nearest_lookup +22.2%/fs=9, exact-lookup=always_dense +15.0%, atlas +86.5%; leave_one_config_out reproduces nearest_lookup +22.2% identically; per-config crossovers: only (1024,4096,4096) wins (0.61-0.86 by block); 128/512 shapes never cross (None); src/generalization.py nearest_config_policy; tests/test_generalization.py (639 tests pass); sparse-lowrank-runtime commit 969deb5a1c941e91cf0ec8e162b732e6ec7198e9; https://github.com/mrcha033/sparse-lowrank-runtime/pull/1; src/fold_robustness.py + tests/test_fold_robustness.py (16 tests); full suite 655 passed; results/l40s_gpu3_bsr_dispatch.json: 3 shapes, 63 points, only (1024,4096,4096) has BSR wins (9/21); decisive-only pooled: parametric +3.2% vs always-dense/lookup/nearest +18.7%; pooled-over-all-folds +2.6% vs +15.0%; training jackknife on decisive shape: slowdown range +0.9%..+6.1% (spread 5.2pp), worst_false_sparse=1 when dropping (512,2048,2048,16); win_capture: 6/9 wins caught, 1.969 of 2.377 ms savings captured (82.8%), missed speedups 1.06/1.20/1.50; RESEARCH_NOTES.md 2026-07-26 robustness entry with reproduce command; PUBLICATION_PATH.md evidence boundary updated; sparse-lowrank-runtime commit be11743facdb7f921c8fa8fdc9ec4a946ad24b8b; https://github.com/mrcha033/sparse-lowrank-runtime/pull/1com/mrcha033/sparse-lowrank-runtime/pull/1)
  • Lesson:dwkv score code contract  + (legacy simulator scoring code, active request queue score breakdown, focused queue tests)
  • Lesson:dwkv failed run fail closed  + (removed failed/partial run manifest, unseeded prompt provenance README, legacy runner tests for fail-closed behavior)
  • Lesson:pivot-b200-20260717-portability-preflight-a01  + (research/EXPERIMENT_PROTOCOL_V1.md; research/CALIBRATION_PIPELINE_V1.md; scripts/pivot_calibration/generation.py; scripts/pivot_experiment/run_plan.py; scripts/pivot_experiment/cell_worker.py; B200-2 read-only preflight on 2026-07-17)
  • Lesson:dwkv legacy patch not repro  + (retracted patch notice, archive README, legacy code README and patch diff)
  • Lesson:dwkv collinear slo confound  + (retracted simulator summary, pre-pivot chronology, corrected independent-mode result comparison)
  • Lesson:dwkv doomed chase domino  + (simulator urgency implementation, SOTA run diagnosis, demote analysis. Hardware numbers are retained only as invalidated provenance.)
  • Lesson:research autopilot 20260722t210001z  + (src/chirp_rate_gate_benchmark.py; results_ … src/chirp_rate_gate_benchmark.py; results_rate_gate.json (334 s CPU, seeds 310..319 disjoint from all prior blocks); lambda=3.0 mean\\|rate\\|: 0.000 at rho=0 vs 0.120 at rho=0.3 (B32/SNR=0); 0.000 vs 0.116 (B16/SNR=0); within-cell frequency spread stays 0.49-0.56; B16/SNR=0 chirplet-minus-best_fixed margins lambda=0->3.0: rho=0 -0.009->+0.001, rho=0.1 -0.060->+0.009, rho=0.3 +0.041->+0.055 (dominates_axis False->True); SNR-gated boundary: at SNR=-5 even lambda=3.0 leaves \\|rate\\|@rho0 at 0.09-0.12 and dominates_axis stays False; 298 tests pass including a lambda=0 bit-for-bit training identity; complex-nn-signal commit 9f879ee72bc75e0c1be88120a5616f4f8628ae11; https://github.com/mrcha033/complex-nn-signal/pull/1e11; https://github.com/mrcha033/complex-nn-signal/pull/1)
원본 주소 "https://s3wiki.yonsei.ac.kr/index.php/특수:속성별검색/:Evidence-20overview/XRP:-20In-2DKernel-20Storage-20Functions-20with-20eBPF.-20OSDI-202022."