Buffer-On-Board Memory System 1 Name: Aurangozeb ISCA 2012

2 Outline Introduction Modern Memory System Buffer-On-Board (BOB) Memory System BOB Simulation Suite BOB Simulation Result Limit-Case Simulation Full System Simulation Conclusion

3 Introduction (1/2) Modification of Memory system to cope with high speed. Dual Inline Memory Module (DIMM) : <100 MHz speed. Signal Integrity (i.e. Cross-talk, Reflection) issue at high speed of operation.  Reduce no. of DIMM to increase CLK speed.  Limits the total capacity One Simple solution: Increase capacity of single DIMM Drawback:  Difficult to decrease DRAM capacitor size.  Cost does not scale linearly

4 Introduction (2/2) FB-DIMM Memory Solution: Advanced Memory Buffer (AMB) with DDRx DRAM to interpret packetized protocol and issue DRAM specific command. Support fast and slow speed of operation. Drawback:  High speed I/O of AMB: Heat & Power issue  Not cost effective Solution from IBM / INTEL / AMD : A single logic chip. Not for one logic chip per FB- DIMM Control DRAM and communicate with CPU over a relatively faster and narrow bus. New architecture using low cost DIMMs

5 Modern Memory System Consideration Ranks of memory per channel DRAM type No. of channels per processor

6 Buffer-On-Board (BOB) Memory System (1/2) Multiple BOB Channels Each Channel consists of LR-, R-, or U-DIMMs Single & Simple controller for each channel Faster and Narrower bus (Link Bus) between simple controller and CPU

7 Buffer-On-Board (BOB) Memory System (2/2) Operation: Request Packet over link bus: Address + Req. Type + Data (if write) Translate Request into DRAM specific command (ACTIVATE, READ, WRITE etc.) and issue to DRAM Ranks. A Command Queue: Dynamic Scheduling Read Return Queue: Sorting after data receive Response Packet contains: Data + Address of initial request. BOB controller: Address mapping Returning data to CPU/Cache Packetizing Request Interpret Response packets: From & To simple controller Encapsulation: to support narrower link bus Use multiple clock to transmit total data. A cross-bar switch: Any port to any link bus.

8 BOB Simulation Suite Two Separate Simulators Developed by authors and MARSSx86 A multi-core x86 simulator developed at SUNY-Binghamton Cycle Based Simulator written in C++ Encapsulate: Main BOB, each BOB, Associated Link and simple controller. Two Modes Stand-alone: Request parameterization, Random address or trace file are issued to memory system Full system simulation: Receive Request from MARSSx86 Memory A DDR (MT41J512M4-187E) A DDR device (MT41J1G4-15E), and A DDR device (MT41J256M4-125E)

9 BOB Simulation Result Two Experiments: A limit-case simulation: random address stream is issued into a BOB memory system. A full system simulation: an operating system is booted on an x86 processor and applications are executed Benchmark NAS parallel benchmarks PARSEC benchmark suite [9] STREAM. Emphasized multi-threaded applications to demonstrate the types of workloads this memory architecture is likely to encounter. Design tradeoffs: Costs such as total pin count, power dissipation, and physical space (or total DIMM count).

10 Limit-Case Simulation Optimal rank depth for each DRAM channel is between 2 and 4 If Return Queue is full, no further read or write. A read return queue must have at least enough capacity for four responses packets. Simple Controller & DRAM Efficiency

Width and speed of buses optimization: No stall the DRAM A read-to-write request ratio of approximately 2-to-1 Equations 1 & 2: Bandwidth required by each link bus to prevent them from negatively impacting the efficiency of each channel. 11 Limit-Case Simulation Link Bus Configuration (1/2)

12 Limit-Case Simulation Weighting the response link bus more than the request : May be ideal for some application Side-effect: Serializing the communication on unidirectional buses Link Bus Configuration (2/2)

13 Limit-Case Simulation Multiple logically independent channels of DRAM to share the same link bus and simple controller Reduce costs such as pin-out, logic fabrication, and physical space. Reduce the number of simple controllers Multi-Channel Optimization

14 Limit-Case Simulation 8 DRAM channels, each with 4 ranks (32 DIMMs making 256 GB total) CPU has up to 128 pins which can be used for data lanes These lanes are operated at 3.2 GHz (6.4 Gb/s) Cost Constrained Simulations

15 Full System Simulations Optimal rank depth for each DRAM channel is between 2 and 4 If Return Queue is full, no further read or write. A read return queue must have at least enough capacity for four responses packets. Simple Controller & DRAM Efficiency

Width and speed of buses optimization: No stall the DRAM A read-to-write request ratio of approximately 2-to-1 Equations 1 & 2: Bandwidth required by each link bus to prevent them from negatively impacting the efficiency of each channel. 16 Limit-Case Simulation Link Bus Configuration (1/2)

17 Limit-Case Simulation Weighting the response link bus more than the request : May be ideal for some application Side-effect: Serializing the communication on unidirectional buses Link Bus Configuration (2/2)

18 Limit-Case Simulation Multiple logically independent channels of DRAM to share the same link bus and simple controller Reduce costs such as pin-out, logic fabrication, and physical space. Reduce the number of simple controllers Multi-Channel Optimization

19 Full System Simulations STREAM and mcol generate the greatest average This is due to the request mix generated during region of interest STREAM: 46% reads and 54% writes mcol: 99% reads. Performance & Power Trade-offs

20 Full System Simulations Performance & Power Trade-offs

21 Full System Simulations Address & Channel Mapping

22 Full System Simulations Address & Channel Mapping

23 Full System Simulations Address & Channel Mapping

24 Conclusion A new memory architecture: Increase both speed and capacity. Intermediate logic between the CPU and DIMMs. Verified by implementing two configurations: Limit-Case Simulation Full System Simulation Queue depths, proper bus configurations, and address mappings are considered to achieve peak efficiency. Cost-constrained simulations are also performed. The buffer-on-board architecture: An ideal near-term solution.