Active Memory Traffic Management for Improving DRAM Energy Efficiency
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Learn how shaping memory traffic can save energy and boost performance in main memory systems, reducing costs and optimizing power management techniques.
Active Memory Traffic Management for Improving DRAM Energy Efficiency
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Presentation Transcript
Improving Energy Efficiency by Making DRAM Less Randomly Accessed Hai Huang, Kang G. Shin, Charles Lefurgy, Tom Keller University of Michigan IBM Austin Research Lab
Overview • Continual increase in the power budget allocated to main memory (i.e., DRAM) • E.g., in a mid-range IBM eServer system, 40% of the total system energy is consumed by its main memory subsystem • By passively monitoring memory traffic and managing the power, existing power management techniques are not fully exploiting deeper power-saving states =>Actively shape memory traffic to enable existing techniques to save more energy
Passive Monitoring Memory Traffic • Why is passively monitoring memory traffic inefficient? • Memory accesses are random – good for performance, bad for energy consumption! • Idle time between consecutive memory accesses is often too short for use of the deeper power-saving state • Randomness is mostly due to OS’s arbitrary virtual-to-physical mapping
Passive memory traffic management Rank 0 Rank 0 Rank 1 Rank 1 time High-power Low-power Ultra Low-power Active memory traffic management time Example: Active vs. Passive
How to Shape Memory Traffic • Essentially, we need to artificially create disparity in access frequency among different memory ranks • Hot Ranks and Cold Ranks • Disparity in access frequency can be created by finding and migrating frequently-accessed pages to a subset of memory ranks • Hot ranks: contain frequently-accessed pages • Cold ranks: contain infrequently-accessed and unmapped pages • Page migration can be done by system software
First level page table Process Second level page table Modify PT Operating System Time triggers Migration thread Migrate (old_page, new_page) Implementation Hot ranks Rank 0 MC page counter Rank 1 Rank 2 Cold ranks Rank 3
Issues with Page Migration • There is a cost associated with each page migration Memory access frequency Is often highly skewed!!! 6% pages causes 75% accesses 14% pages causes 90% accesses Not all pages need to be migrated
Evaluation • Simulators • Mambo [IBM] – A full-machine simulator, cycle-accurate, supports PowerPC architecture • Memsim [IBM] – Detailed trace-driven main memory simulator, written in CSIM • Workloads • Low memory-intensive workload: SPECjbb + bzip + crafty • High memory-intensive workload: SPECjbb + art + mcf • SPECjbb: simulating 8 warehouses • SPEC2000 benchmarks: using Reference input set
Summary of Results • Energy: • Actively shaping memory traffic saves 35% more energy than passively monitoring • Performance: • Low memory-intensive workload: small impact on performance • High memory-intensive workload: significantly degrades performance due to more contention on hot ranks • Cost: • Use hardware counters, or • Software page faults
Conclusion • Actively shaping memory traffic allows existing power management techniques to more effectively save power • Highly-skewed page accesses are observed • Alternative main memory design: • Use high-performance/highly-parallel ranks as hot ranks • Use low-performance/low-power ranks as cold ranks • Allows frequently-accessed pages to be accessed faster • Allows memory ranks that hold infrequently-accessed and unmapped pages to consume less energy
