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Bryan S. Kim

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titleconferencedate
Preparation Meets Opportunity: Enhancing Data Preprocessing for ML Training With SenecaFAST '262026-02-24
Seneca is a modified PyTorch dataloader that uses model-driven partitioning to split DRAM between encoded, decoded, and augmented forms and opportunistic data…
Talk on
The Design and Implementation of a Capacity-Variant Storage System22nd USENIX Conference on File and Storage Technologies (FAST '24)2024-02-27
A capacity-variant storage system (CVSS) is implemented atop Linux 5.15 with CV-FS (F2FS baseline), CV-SSD and a user-space CV-manager that coordinates…
Talk on
Overcoming the Memory Wall with CXL-Enabled SSDUSENIX ATC '232023-07-10
Study builds a physical memory tracer and a trace-driven simulator to model CXL-enabled SSDs and integrates a DRAM cache, MSHR and several prefetchers to…
Talk
Generating Realistic Wear Distributions for SSDs (Work-in-Progress Report)FAST '222022-02-22
A machine-learning aging framework samples real workloads in a simulator, builds lightweight per-block regression models from observed internal SSD activity…
Talk on
Overcoming Capacitance Constraints in SSD (Work-in-Progress Report)FAST '222022-02-22
Proposes a divided-architecture SSD that avoids full capacitor-backed PRP by protecting only 1% of mapping entries and forcing cold mapping pages to land in…
Talk
Modernizing File System through In-Storage Indexing15th USENIX Symposium on Operating Systems Design and Implementation (OSDI '21)2021-07-14
KEVIN replaces the block interface with a host-side lightweight POSIX file system that maps files to inode-based keys (meta keys prefixed m, data keys prefixed…
Talk on
Design Tradeoffs for SSD ReliabilityFAST '192019-02-25
Measured raw bit error rates rise sharply across generations, and uncoordinated use of data re-read, intra-SSD redundancy, and scrubbing drives big slowdowns…
Talk
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