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결과 목록

Lesson:fast flexible and practical kernel extensions 9eb8897f + (Scope verification to shared critical resources and enforce private-state safety with cheaper runtime controls.)
Lesson:rl watchdog a fast and predictable ssd liveness watchdog on storage systems a9a43b61 + (Separate a cheap health signal from adaptive failure policy and connect it to rapid recovery.)
Lesson:agile lightweight and efficient asynchronous gpu ssd integration e7527db8 + (Separate submission from completion and dedicate device-local progress so application warps never hold blocking resources.)
Lesson:bind only vllm rpc sockets to a short private path 4bf9d75f + (Set VLLM_RPC_BASE_PATH explicitly to a sho … Set VLLM_RPC_BASE_PATH explicitly to a short owner-only directory and leave TMPDIR/JIT caches on their intended executable private mount. Budget the complete encoded socket path, record the controlled environment semantically, and terminate/verify the full process group before deleting the RPC directory.s group before deleting the RPC directory.)
Lesson:rfuse modernizing userspace filesystem framework through scalable kernel userspace communication b3196db3 + (Shard cross-boundary queues by core and preserve compatibility above the transport layer.)
Lesson:pivot-b200-20260717-launch-lock-a01 + (Source-bound experiment lock directories inside the repository must be explicitly ignored; otherwise a post-lock clean-tree check is guaranteed to fail on its own owner metadata.)
Lesson:legoos a disseminated distributed os for hardware resource disaggregation d71e3e68 + (Split kernel services along hardware ownership boundaries while preserving a familiar application abstraction.)
Lesson:taming throughput latency tradeoff in llm inference with sarathi serve cf395778 + (Split long, bursty stages into schedulable chunks and co-batch them with steady-state work.)
Lesson:mitigating resource usage dependency in sorting based kv stores on hybrid storage devices via op 31cbb8ad + (Split metadata evolution from immutable payload placement when their update lifecycles differ.)
Lesson:extmem enabling application aware virtual memory management for data intensive applications 8a6dc0e4 + (Standardize the extension boundary before optimizing individual policies.)
Lesson:not a dpu in name only unleashing rdma capable dpus in multi tenant serverless clouds with nadin 7031318c + (Terminate ingress near RDMA and preserve zero-copy semantics across tenancy boundaries.)
Lesson:chrono meticulous hotness measurement and flexible page migration for memory tiering 840ae980 + (Timer-derived idle intervals decouple useful hotness resolution from aggressive sampling; distribution-aware tuning makes migration responsive while limiting churn.)
Lesson:m5 mastering page migration and memory management for cxl based tiered memory systems 4e752168 + (Track activity at both allocation and transfer granularity when hotness is spatially sparse.)
Lesson:hotrap hot record retention and promotion for lsm trees with tiered storage 849aa350 + (Track and move the smallest independently valuable hot unit.)
Lesson:nomad non exclusive memory tiering via transactional page migration 3990fa86 + (Trade modest capacity for a recoverable shadow when it removes expensive synchronous movement.)
Lesson:technical review a fully associative tagless dram cache 8377cc32 + (Translation과 cache-location lookup을 하나의 mapping으로 통합하면 tag lookup과 tag storage를 함께 제거할 수 있다.)
Lesson:a fully associative tagless dram cache f6383680 + (Translation과 cache-location lookup을 하나의 mapping으로 통합하면 tag lookup과 tag storage를 함께 제거할 수 있다.)
Lesson:unimem redesigning disaggregated memory within a unified local remote memory hierarchy 4e1d18c6 + (Treat cache placement, translation, and migration as one hierarchy-wide policy.)
Lesson:shiftlock mitigate one sided rdma lock contention via handover a5d67e63 + (Under high contention, hand work directly to a known successor instead of reopening global competition.)
Lesson:unicom a universally high performant i o completion mechanism for modern computer systems 9172fe3e + (Unify completion modes behind load-aware scheduling and preserve per-request identity.)
Lesson:utopia fast and efficient address translation via hybrid restrictive flexible virtual to physica 796873cf + (Use a fast constrained path for suitable objects and retain a flexible escape path.)
Lesson:pivot-b200-20260717-venv-launcher-identity-a01 + (Use an absolute but non-resolved <venv>/bin/python path for subprocess launch. Never resolve the launcher symlink; test sys.prefix or a real CLI guard under the exact safe-path/PYTHONPATH environment before GPU work.)
Lesson:avoiding read stalls on flash storage 34c6809a + (Use bounded staging to decouple latency-critical allocation from slow durable writeback.)
Lesson:corobase coroutine oriented main memory database engine c4a28018 + (Use coroutines to interleave independent requests around predictable long-latency accesses.)
Lesson:kvaccel a novel write accelerator for lsm tree based kv stores with host ssd collaboration 968f5966 + (Use device interfaces according to data lifetime and write-path urgency, with an explicit reconciliation protocol.)

Lesson:telescope telemetry for gargantuan memory footprint applications 6a766ffb + (Use hierarchy to prune monitoring work at extreme scale.)

Lesson:faasmem improving memory efficiency of serverless computing with memory pool architecture b6ab9eec + (Use object-lifecycle phases to segment and tier state instead of treating all pages alike.)
Lesson:cacheblend fast large language model serving for rag with cached knowledge fusion 056a5f5e + (Use selective correction between exact recomputation and unsafe cache reuse.)
Lesson:technical review virtual asymmetric multiprocessor for interactive performance of consolidated d 70c3d6f5 + (VM 단위 우선순위만으로는 intra-VM QoS를 보장하기 어렵고, 작업 의미를 추론해 vCPU share와 guest 배치를 함께 조정해야 한다.)
Lesson:virtual asymmetric multiprocessor for interactive performance of consolidated desktops ec394686 + (VM 단위 우선순위만으로는 intra-VM QoS를 보장하기 어렵고, 작업 의미를 추론해 vCPU share와 guest 배치를 함께 조정해야 한다.)
Lesson:technical review transparently bridging semantic gap in cpu management for virtualized environme ddf55f9b + (VMM이 guest를 수정하지 않더라도 hardware/event timing에서 최소 의미를 추론하면 resource scheduling을 workload-aware하게 만들 수 있다.)
Lesson:transparently bridging semantic gap in cpu management for virtualized environments 2485a772 + (VMM이 guest를 수정하지 않더라도 hardware/event timing에서 최소 의미를 추론하면 resource scheduling을 workload-aware하게 만들 수 있다.)
Lesson:vfpio a virtual i o abstraction for fpga accelerated i o devices dcc63d73 + (Virtualize heterogeneous I/O around a shared scheduling abstraction, not device-specific queues.)
Lesson:impress an importance informed multi tier prefix kv storage system for large language model infe 51b47015 + (When cached state is too large to reload, rank units by output importance and tier them accordingly.)
Lesson:specinfer accelerating generative large language model serving with tree based speculative infer e609aa25 + (When cheap predictors are uncertain, aggregate diverse candidates and verify them in one expensive parallel pass.)
Lesson:technical review an adaptive zone grouping scheme enabling general purpose file systems on zns s 21d78705 + (ZNS의 물리 zone을 논리 그룹으로 추상화하되 그룹 크기를 고정 상수로 두지 말고 현재 병렬성과 reclaim 요구에 맞춰야 한다.)
Lesson:an adaptive zone grouping scheme enabling general purpose file systems on zns ssds c91eb86f + (ZNS의 물리 zone을 논리 그룹으로 추상화하되 그룹 크기를 고정 상수로 두지 말고 현재 병렬성과 reclaim 요구에 맞춰야 한다.)
Lesson:research autopilot 20260723t090001z-gpu + (algebraic-ml-compiler: Do not repeat this experiment without a changed hypothesis; reuse the measured scientific verdict and device-specific bounds.)
Lesson:research autopilot 20260723t030001z + (alpha-factory: A diversification finding t … alpha-factory: A diversification finding that depends on one lineage escaping a fitness/decorrelation admission cap can be entirely universe-specific: verify transfer by regenerating the frozen protocol on a separate universe and inspecting the admission trace (carrying-sleeve standalone fitness and runner-up correlation to the elite) BEFORE spending any sealed hidden-test access. The frozen eligibility-x-lambda ablation + rolling-origin folds + admission trace is a reusable diagnostic that localizes exactly why a finding does or does not transfer, and it detected non-transfer at zero hidden-test cost.ted non-transfer at zero hidden-test cost.)
Lesson:research autopilot 20260721t210001z + (alpha-factory: Before treating a favorable … alpha-factory: Before treating a favorable single-window backtest bootstrap as a transferable edge, replay the exact frozen rule across independent non-overlapping outer windows and pool them as one rolling-origin backtest; separate the STRUCTURAL claim (composition/eligibility that is window-independent by construction) from the ECONOMIC-MAGNITUDE claim (risk-adjusted return), because the former can replicate cleanly while the latter is concentrated in one regime. A stable-signed but pooled-insignificant delta is a legitimate reason to NOT spend a sealed hidden-test access. to NOT spend a sealed hidden-test access.)
Lesson:research autopilot 20260720t090001z + (alpha-factory: When an ensemble or portfol … alpha-factory: When an ensemble or portfolio collapses to one lineage, diagnose which pipeline stage is binding before tuning any selection-stage knob: a diversity bonus at selection is arithmetically irrelevant if upstream per-candidate quality gates already removed the decorrelated candidates. Test eligibility and selection changes as a factorial rather than sequentially, because either alone can read as a null result while their interaction carries the whole effect. When relaxing gates, partition them explicitly into role-specific quality gates (bypassable, since a hedge underperforms benchmarks by construction) versus safety gates (never bypassable), and verify selectivity by checking that an attractive-looking candidate failing a safety gate is still refused. complex-nn-signal: When benchmarking a learned detector against a classical one, control inference budget (number of correlations/evaluations per example) rather than parameter count — once the classical method must search, compute is the scarce resource and parameter-matching measures the wrong thing. Decompose any apparent neural advantage into placement (where the basis functions sit) and combiner (how their outputs are pooled) with an arm that varies only one at a time; here the entire effect lived in the combiner. Diagnose a trained arm losing to a parameter-free arm by comparing TRAIN accuracies — if the trained arm underfits the parameter-free one, the deficit is expressivity, not generalization, and adding data or regularization will not help. Expect learned bases to help when the true support is sparse and discrete (they concentrate on it) and to be inert when the support is a continuum (the uniform grid is already optimal, so gradient descent only adds placement scatter). azure_inference_queueing: Two reusable items. (1) Before building a joint optimizer for a coupled item-selection plus variant-choice problem, check where the cheap variant's weight multiplier sits relative to 1/2 of the full weight: at m <= 1/2 the coupled problem provably degenerates to the decoupled one, the nesting constraint never binds, and single-variant approximation theory transfers with a strictly tighter constant. Adding a cheap-variant dimension can NARROW rather than widen a greedy optimality gap, because the smaller variant improves packing granularity — the opposite of the natural intuition. (2) When a theorem yields a structural ordering condition, never report it as a prediction of the realized event without including the resource constraint in the test: an ordering can hold on ~50% of instances while the corresponding realized event occurs on 0%, because realizing it also requires the capacity to reach that point. Keep the structural quantity and the realized quantity in separate reported fields; conflating them is a repeatable, self-inflicted falsification. gaussian-3mul-compiler: Two reusable lessons. (1) When evaluating whether a hardware primitive such as FMA favours one algebraic formulation over another, check whether the supposedly disadvantaged formulation can also use the primitive - here the Karatsuba-style 3-mul's combining product was fusable, which neutralised the entire predicted effect. Comparing a contracted baseline against an un-contracted candidate is a rigged comparison. (2) For floating-point error studies, report medians and quantiles, never sample means: relative FP error is heavy-tailed and mean ratios are dominated by rare near-cancellation samples. Verify any error-ratio effect with a seed-stability check across at least five seeds before believing it - in this study an exploratory mean-based run produced a number that supported the hypothesis the stable estimator then refuted. the stable estimator then refuted.)
Lesson:research autopilot 20260721t090001z + (alpha-factory: When an evaluator-semantics … alpha-factory: When an evaluator-semantics fix (excluding a hidden suffix) invalidates prior artifacts, regenerate and re-test rather than assuming the old conclusion breaks: check whether the affected quantity (here candidate-level total_return/fitness over the full range) actually feeds the reported conclusion (here an OOS window that structurally never overlapped the hidden suffix). Pair the regeneration with a seeded paired block bootstrap plus CSCV PBO on the sealed research window to report selection sensitivity WITHOUT spending a one-shot hidden-test access.UT spending a one-shot hidden-test access.)
Lesson:research autopilot 20260721t150001z + (azure_inference_queueing: To generalize a … azure_inference_queueing: To generalize a single-constraint knapsack integrality-gap certificate to m constraints, use the bounded-variable-LP basic-solution property: a vertex has at most m fractional variables, so rounding them down yields a feasible integer solution and LP*−IP* ≤ sum of the (≤m) fractional item values. Force a vertex solver (scipy linprog method='highs-ds' dual simplex) — the default 'highs' can dispatch to interior-point and return a non-basic point with more than m fractional coordinates, spuriously breaking the structural claim. The relaxation certificate generalizes cleanly even when the greedy-optimality argument does not.ity argument does not.)
Lesson:combining buffered i o and direct i o in distributed file systems b0e268e6 + (buffered/direct 선택을 애플리케이션 설정이 아닌 런타임 정책으로 만들라.)
Lesson:automatically reasoning about how systems code uses the cpu cache 11306b93 + (cache 분석은 단일 trace가 아니라 입력→footprint/miss의 모델로 표현하라.)
Lesson:technical review scoz a system wide causal profiler for multicore systems 9ddaf48a + (causal profiling의 범위를 넓히려면 프로세스가 아니라 CPU core를 공통 관측·지연 단위로 삼되 idle dependency와 migration semantics를 함께 고쳐야 한다.)
Lesson:scoz a systemwide causal profiler for multicore systems 7b5e72e2 + (causal profiling의 범위를 넓히려면 프로세스가 아니라 CPU core를 공통 관측·지연 단위로 삼되 idle dependency와 migration semantics를 함께 고쳐야 한다.)
Lesson:technical review task aware virtual machine scheduling for i o performance 26a8da47 + (coarse VM-level boost를 task/event 기간으로 축소하고 사용량 cap을 두면 intra-VM heterogeneity를 다룰 수 있다.)
Lesson:task aware virtual machine scheduling for i o performance f431ccbe + (coarse VM-level boost를 task/event 기간으로 축소하고 사용량 cap을 두면 intra-VM heterogeneity를 다룰 수 있다.)
Lesson:research autopilot 20260722t210001z + (complex-nn-signal: An L1 penalty on an opt … complex-nn-signal: An L1 penalty on an optional model degree of freedom behaves as a data-adaptive gate: because it competes against a cross-entropy data-gradient whose magnitude scales with how useful that DOF is for the training distribution, one fixed penalty weight nulls the DOF where it is useless and keeps it where it is load-bearing. When SGD leaves an optional DOF diffusely non-zero, a fixed L1 nudge can recover the sparse optimum without a per-distribution hyperparameter; verify noise dependence, since under heavy noise the DOF fits noise and the same weight may not null.ts noise and the same weight may not null.)
Lesson:dwkv collinear slo confound + (deadline-aware scheduler를 평가할 때 priority/value와 deadline budget을 독립적으로 변동시키고, collinear boundary case는 본 결과가 아니라 별도 diagnostic으로 표시한다.)