Penn ESE534 Spring2012 -- DeHon 1 ESE534: Computer Organization Day 7: February 6, 2012 Memories.

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Presentation transcript:

Penn ESE534 Spring DeHon 1 ESE534: Computer Organization Day 7: February 6, 2012 Memories

Penn ESE534 Spring DeHon 2 Previously… Arithmetic: addition, subtraction Reuse: –pipelining –bit-serial (vectorization) Area/Time Tradeoffs Latency and Throughput

Penn ESE534 Spring DeHon 3 Today Memory –features –Area and delay intuition and modeling –design –technology

Preclass 1 Penn ESE534 Spring DeHon 4 When is:

Preclass 2 Penn ESE534 Spring DeHon 5 Find m to minimize:

Preclass 2 How related? Penn ESE534 Spring DeHon 6

Preclass 2 Related? m=bw bw*bd=N –So bd=N/m Penn ESE534 Spring DeHon 7

Preclass 2 C 3 is for area of single memory cell log 2 (n) is for decoder –In red C 1 is for gates in decoder C 2 is for amps at bottom of row and drivers at top Penn ESE534 Spring DeHon 8

Preclass 1 Penn ESE534 Spring DeHon 9 When we solved for N, we found m is proportional to √N If we approximate log 2 (N) as a constant, we get

Preclass 3, 4 Delay –Scale with bd? –Scale with bw? Penn ESE534 Spring DeHon 10

Penn ESE534 Spring DeHon 11 Memory What’s a memory? What’s special about a memory?

Penn ESE534 Spring DeHon 12 Memory Function Typical: –Data Input Bus –Data Output Bus –Address (location or name) –read/write control

Penn ESE534 Spring DeHon 13 Memory Block for storing data for later retrieval State element

Collection of Registers What’s different between a memory and a collection of registers? Penn ESE534 Spring DeHon 14

Penn ESE534 Spring DeHon 15 Memory Uniqueness Cost Compact state element Packs data very tightly At the expense of sequentializing access Example of Area-Time tradeoff –and a key enabler

Penn ESE534 Spring DeHon 16 Memory Organization Key idea: sharing –factor out common components among state elements –can have big elements if amortize costs –state element unique  small word lines Bit lines

Penn ESE534 Spring DeHon 17 SRAM Memory bit Source:

Penn ESE534 Spring DeHon 18 Memory Organization Share: Interconnect –Input bus –Output bus –Control routing very topology/wire cost aware design Note: local, abuttment wiring

Penn ESE534 Spring DeHon 19 Share Interconnect Input Sharing –wiring –drivers Output Sharing –wiring –sensing –driving

Penn ESE534 Spring DeHon 20 Address/Control Addressing and Control –an overhead –paid to allow this sharing

Penn ESE534 Spring DeHon 21 Memory Organization

Penn ESE534 Spring DeHon 22 Dynamic RAM Goes a step further Share refresh/restoration logic as well Minimal storage is a capacitor “Feature” DRAM process is ability to make capacitors efficiently

Penn ESE534 Spring DeHon 23 Some Numbers (memory) Unit of area = 2 (F=2  –[more next week] Register as stand-alone element  4K 2 –e.g. as needed/used last lecture Static RAM cell  1K 2 –SRAM Memory (single ported) Dynamic RAM cell (DRAM process)  Dynamic RAM cell (SRAM process)  300 2

DRAM Layout Penn ESE534 Spring DeHon 24 Source: bitline wordline

Penn ESE534 Spring DeHon 25 DRAM Latency µProc 60%/yr. DRAM 7%/yr DRAM CPU 1982 Processor-Memory Performance Gap: (grows 50% / year) Performance Time “Moore’s Law” [From Patterson et al., IRAM:

Penn ESE534 Spring DeHon 26 Contemporary DRAM 1GB DDR3 SDRAM from Micron – –96 pin pakage –16b datapath IO –Operate at 500+MHz –37.5ns random access latency

Penn ESE534 Spring DeHon 27 Memory Access Timing RAS/CAS access Optimization for access within a row

Penn ESE534 Spring DeHon 28 Contemporary DRAM 1GB DDR3 SDRAM from Micron – –96 pin pakage –16b datapath IO –Operate at 500+MHz –37.5ns random access latency

Penn ESE534 Spring DeHon 29 1 Gigabit DDR2 SDRAM [Source:

Penn ESE534 Spring DeHon 30 Contemporary DRAM 4GB DDR3 SDRAM from Micron – es/ddr3/ksf16c256_512x64hz.pdfhttp://download.micron.com/pdf/datasheets/modul es/ddr3/ksf16c256_512x64hz.pdf –Operate at 800MHz –50ns random access latency

Penn ESE534 Spring DeHon 31 DRAM Latency µProc 60%/yr. DRAM 7%/yr DRAM CPU 1982 Processor-Memory Performance Gap: (grows 50% / year) Performance Time “Moore’s Law” [From Patterson et al., IRAM:

Penn ESE534 Spring DeHon 32 Basic Memory Design Space Width Depth Internal vs. External Width Banking –To come

Penn ESE534 Spring DeHon 33 Depth What happens as make deeper? –Delay? –Energy?

Penn ESE534 Spring DeHon 34 Banking Tile Banks/memory blocks What does banking do for us? (E, D, A)?

Penn ESE534 Spring DeHon 35 Independent Bank Access Utility? Costs and benefits?

Penn ESE534 Spring DeHon 36 Memory Key Idea –Memories hold state compactly –Do so by minimizing key state storage and amortizing rest of structure across large array

Penn ESE534 Spring DeHon 37 Yesterday vs. Today (Memory Technology) What’s changed?

Penn ESE534 Spring DeHon 38 Yesterday vs. Today (Memory Technology) What’s changed? –Capacity single chip –Integration memory and logic dram and logic embedded memories –Room on chip for big memories And many memories… –Don’t have to make a chip crossing to get to memory [Patterson et al., IEEE Micro April 1997]

Penn ESE534 Spring DeHon 39 Important Technology Cost IO between chips << IO on chip –pad spacing –area vs. perimeter (4s vs. s 2 ) –wiring technology BIG factor in multi-chip system designs Memories nice –very efficient with IO cost vs. internal area

Penn ESE534 Spring DeHon 40 On-Chip vs. Off-Chip BW Use Micron 1Gb DRAM as example On Chip BW: assume b banks? assume independent 1024 × 1024b banks?

Memory on a Virtex-6 40nm process node –Last generation, 28nm sampling now 300,000 programmable 6-input gates ( 6-LUTs ) 1,064 memory banks ~ 512×72 –Total ~ 38Mbits Operating at 600MHz On chip bandwidth? Penn ESE534 Spring DeHon 41 [image from

Penn ESE534 Spring DeHon 42 Costs Change Design space changes when whole system goes on single chip Can afford –wider busses –more banks –memory tailored to application/architecture Beware of old (stale) answers –their cost model was different

Penn ESE534 Spring DeHon 43 What is Importance of Memory? Radical Hypothesis: –Memory is simply a very efficient organization which allows us to store data compactly (at least, in the technologies we’ve seen to date) –A great engineering trick to optimize resources Alternative: –memory is a primary State is a primary, but state≠memory

Penn ESE534 Spring DeHon 44 Admin HW1 and 2 graded – note feedback (even if received perfect score) HW4 out today Reading –Was for today –Nothing new for Wed., Mon. Office Hours: Tuesday 4:15pm

Penn ESE534 Spring DeHon 45 Big Ideas [MSB Ideas] Memory: efficient way to hold state Resource sharing: key trick to reduce area Memories are a great example of resource sharing

Penn ESE534 Spring DeHon 46 Big Ideas [MSB-1 Ideas] Tradeoffs in memory organization Changing cost of memory organization as we go to on-chip, embedded memories