Data-intensive applications move large amounts of data from storage to the compute unit, incurring significant data movement overhead. Storage-centric computing reduces this overhead by moving computation near or inside solid-state drives (SSDs). Enabling it requires modifying SSD policies, e.g., address translation an...
Harshita Gupta, Mayank Kabra, Rakesh Nadig et al.· 0 citations
DCC is the first data-centric ML compiler for PIM systems that jointly co-optimizes data rearrangements and compute code in a unified tuning process to enable high performance execution.
Pei-Ming Yang, Sankeerth Durvasula, Ivan Fernandez et al.· International Symposium on C...· 1 citation
FLINT is proposed, a workload-driven HBF substrate for capacity-scalable LLM inference that integrates HBF as a memory-capacity tier alongside HBM while addressing three adoption challenges.
Geraldo F. Oliveira, Arash Tavakkol, Xiang-Yu Zhu et al.· 1 citation
Analysis of HBF-based LLM-serving systems under diverse system configurations and operating scenarios shows that HBF can significantly improve the batch size, throughput, and flexibility of LLM-serving systems while reducing the minimum GPU requirements, but realizing these benefits critically depends on sustaining HBM...
D. Son, Yonggon Park, Hyunuk Cho et al.· IEEE computer architecture l...· 2 citations
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