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JAFAR : Near-Data Processing for Databases Oreoluwa Babarinsa and Stratos Idreos Why Soſtware Soluons aren’t Sufficient Near-Data Processing JAFAR Design Experimental Results Future Work Movaon Main Memory sizes are Moving data from main memory into Fabricaon advances have made We could potenally surpass the memory We achieve up to a 9x speed up depending on data size Speedup is linearly correlated with query selecvity JAFAR, : simple yet effecve NDP Selecons Lives on the DRAM module Two ALUs for comparisons Write output to a page size buffer Opcodes programmed by CPU Develop similar hardware to han- dle more DB operators Invesgate how to break the memory wall without breaking the memory abstracon NDP moves computaon down to memory hierarchy Reduce memory bus ulizaon Frees CPU to do other useful work New opportunies for DB architectures Fundamentally, all algorithmic and soſtware soluons to the memory wall sll requires moving data upstream in the memory hierarchy daslab.seas.harvard.edu

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JAFAR : Near-Data Processing for Databases

Oreoluwa Babarinsa and Stratos Idreos

Why Software Solutions aren’t Sufficient Near-Data Processing

JAFAR Design Experimental Results

Future Work

Motivation

Main Memory sizes are Moving data from main memory into Fabrication advances have made We could potentially surpass the memory

We achieve up to a 9x speed up

depending on data size

Speedup is linearly correlated

with query selectivity

JAFAR, : simple yet effective NDP Selections

Lives on the DRAM module

Two ALUs for comparisons

Write output to a page size buffer

Opcodes programmed by CPU

Develop similar hardware to han-

dle more DB operators

Investigate how to break the memory

wall without breaking the memory

abstraction

NDP moves computation down to memory hierarchy

Reduce memory bus utilization

Frees CPU to do other useful work

New opportunities for DB architectures Fundamentally, all algorithmic and software solutions to the

memory wall still requires moving data upstream in the

memory hierarchy

daslab.seas.harvard.edu