Title: Memory Subsystem and Cache
1Memory Subsystem and Cache
- Adapted from lectures notes of Dr. Patterson and
Dr. Kubiatowicz of UC Berkeley
2The Big Picture
Processor
Input
Control
Memory
Datapath
Output
3Technology Trends
Capacity Speed (latency) Logic 2x
in 3 years 2x in 3 years DRAM 4x in 3
years 2x in 10 years Disk 4x in 3 years 2x
in 10 years
DRAM Year Size Cycle
Time 1980 64 Kb 250 ns 1983 256 Kb 220 ns 1986 1
Mb 190 ns 1989 4 Mb 165 ns 1992 16 Mb 145
ns 1995 64 Mb 120 ns
10001!
21!
4Technology Trends contd
Processor-DRAM Memory Gap (latency)
µProc 60/yr. (2X/1.5yr)
1000
CPU
Moores Law
100
Processor-Memory Performance Gap(grows 50 /
year)
10
Less Law?
DRAM 9/yr. (2X/10 yrs)
DRAM
1
1980
1981
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
1982
Time
5The Goal Large, Fast, Cheap Memory !!!
- Fact
- Large memories are slow
- Fast memories are small
- How do we create a memory that is large, cheap
and fast (most of the time) ? - Hierarchy
- Parallelism
6- By taking advantage of the principle of locality
- Present the user with as much memory as is
available in the cheapest technology. - Provide access at the speed offered by the
fastest technology.
Processor
Control
Secondary Storage (Disk)
Main Memory (DRAM)
Second Level Cache (SRAM)
On-Chip Cache
Datapath
Registers
10,000,000ns (10 ms)
1s
Speed (ns)
10ns
100ns
10,000,000,000ns (10 sec)
100s
Gs
Size (bytes)
Ks
Ms
Ts
7Todays Situation
- Rely on caches to bridge gap
- Microprocessor-DRAM performance gap
- time of a full cache miss in instructions
executed - 1st Alpha (7000) 340 ns/5.0 ns  68 clks x 2
or 136 instructions - 2nd Alpha (8400) 266 ns/3.3 ns  80 clks x 4
or 320 instructions
8Memory Hierarchy (1/4)
- Processor
- executes programs
- runs on order of nanoseconds to picoseconds
- needs to access code and data for programs where
are these? - Disk
- HUGE capacity (virtually limitless)
- VERY slow runs on order of milliseconds
- so how do we account for this gap?
9Memory Hierarchy (2/4)
- Memory (DRAM)
- smaller than disk (not limitless capacity)
- contains subset of data on disk basically
portions of programs that are currently being run - much faster than disk memory accesses dont slow
down processor quite as much - Problem memory is still too slow(hundreds of
nanoseconds) - Solution add more layers (caches)
10Memory Hierarchy (3/4)
Higher
Lower
11Memory Hierarchy (4/4)
- If level is closer to Processor, it must be
- smaller
- faster
- subset of all higher levels (contains most
recently used data) - contain at least all the data in all lower levels
- Lowest Level (usually disk) contains all
available data
12Analogy Library
- Youre writing a term paper (Processor) at a
table in Evans - Evans Library is equivalent to disk
- essentially limitless capacity
- very slow to retrieve a book
- Table is memory
- smaller capacity means you must return book when
table fills up - easier and faster to find a book there once
youve already retrieved it
13Analogy Library contd
- Open books on table are cache
- smaller capacity can have very few open books
fit on table again, when table fills up, you
must close a book - much, much faster to retrieve data
- Illusion created whole library open on the
tabletop - Keep as many recently used books open on table as
possible since likely to use again - Also keep as many books on table as possible,
since faster than going to library
14Memory Hierarchy Basics
- Disk contains everything.
- When Processor needs something, bring it into to
all lower levels of memory. - Cache contains copies of data in memory that are
being used. - Memory contains copies of data on disk that are
being used. - Entire idea is based on Temporal Locality if we
use it now, well want to use it again soon (a
Big Idea)
15Caches Why does it Work ?
- Temporal Locality (Locality in Time)
- gt Keep most recently accessed data items closer
to the processor - Spatial Locality (Locality in Space)
- gt Move blocks consists of contiguous words to
the upper levels
16Cache Design Issues
- How do we organize cache?
- Where does each memory address map to? (Remember
that cache is subset of memory, so multiple
memory addresses map to the same cache location.) - How do we know which elements are in cache?
- How do we quickly locate them?
17Direct Mapped Cache
- In a direct-mapped cache, each memory address is
associated with one possible block within the
cache - Therefore, we only need to look in a single
location in the cache for the data if it exists
in the cache - Block is the unit of transfer between cache and
memory
18Direct Mapped Cache contd
- Cache Location 0 can be occupied by data from
- Memory location 0, 4, 8, ...
- In general any memory location that is multiple
of 4
19Issues with Direct Mapped Cache
- Since multiple memory addresses map to same cache
index, how do we tell which one is in there? - What if we have a block size gt 1 byte?
- Result divide memory address into three fields
20Example of a direct mapped cache
- For a 2N byte cache
- The uppermost (32 - N) bits are always the Cache
Tag - The lowest M bits are the Byte Select (Block Size
2M)
Block address
0
4
31
9
Cache Index
Cache Tag
Example 0x50
Byte Select
Ex 0x01
Ex 0x00
Stored as part of the cache state
Cache Data
Valid Bit
Cache Tag
0
Byte 0
Byte 1
Byte 31
1
0x50
Byte 32
Byte 33
Byte 63
2
3
31
Byte 992
Byte 1023
21Terminology
- All fields are read as unsigned integers.
- Index specifies the cache index (which row of
the cache we should look in) - Offset once weve found correct block, specifies
which byte within the block we want - Tag the remaining bits after offset and index
are determined these are used to distinguish
between all the memory addresses that map to the
same location
22Terminology contd
- Hit data appears in some block in the upper
level (example Block X) - Hit Rate the fraction of memory access found in
the upper level - Hit Time Time to access the upper level which
consists of - RAM access time Time to determine hit/miss
- Miss data needs to be retrieve from a block in
the lower level (Block Y) - Miss Rate 1 - (Hit Rate)
- Miss Penalty Time to replace a block in the
upper level - Time to deliver the block the processor
- Hit Time ltlt Miss Penalty
Lower Level Memory
Upper Level Memory
To Processor
Blk X
From Processor
Blk Y
23How is the hierarchy managed ?
- Registers lt-gt Memory
- by compiler (programmer?)
- cache lt-gt memory
- by the hardware
- memory lt-gt disks
- by the hardware and operating system (virtual
memory) - by the programmer (files)
24Example
- Suppose we have a 16KB of data in a direct-mapped
cache with 4 word blocks - Determine the size of the tag, index and offset
fields if were using a 32-bit architecture - Offset
- need to specify correct byte within a block
- block contains 4 words 16 bytes 24
bytes - need 4 bits to specify correct byte
25Example contd
- Index (index into an array of blocks)
- need to specify correct row in cache
- cache contains 16 KB 214 bytes
- block contains 24 bytes (4 words)
- rows/cache blocks/cache (since theres
one block/row) bytes/cache bytes/row
214 bytes/cache 24 bytes/row
210 rows/cache - need 10 bits to specify this many rows
26Example contd
- Tag use remaining bits as tag
- tag length mem addr length -
offset - index 32 - 4 -
10 bits 18 bits - so tag is leftmost 18 bits of memory address
27Accessing data in cache
Memory
Value of Word
Address (hex)
- Ex. 16KB of data, direct-mapped, 4 word blocks
- Read 4 addresses
- 0x00000014, 0x0000001C, 0x00000034, 0x00008014
- Memory values on right
- only cache/memory level of hierarchy
28Accessing data in cache contd
- 4 Addresses
- 0x00000014, 0x0000001C, 0x00000034, 0x00008014
- 4 Addresses divided (for convenience) into Tag,
Index, Byte Offset fields
000000000000000000 0000000001 0100 000000000000000
000 0000000001 1100 000000000000000000 0000000011
0100 000000000000000010 0000000001 0100 Tag
Index Offset
2916 KB Direct Mapped Cache, 16B blocks
- Valid bit determines whether anything is stored
in that row (when computer initially turned on,
all entries are invalid)
Index
30Read 0x00000014 000 0..001 0100
- 000000000000000000 0000000001 0100
Offset
Index field
Tag field
Index
31So we read block 1 (0000000001)
- 000000000000000000 0000000001 0100
Tag field
Index field
Offset
Index
32No valid data
- 000000000000000000 0000000001 0100
Tag field
Index field
Offset
Index
33So load that data into cache, setting tag, valid
- 000000000000000000 0000000001 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
34Read from cache at offset, return word b
- 000000000000000000 0000000001 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
35Read 0x0000001C 000 0..001 1100
- 000000000000000000 0000000001 1100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
36Data valid, tag OK, so read offset return word d
- 000000000000000000 0000000001 1100
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
37Read 0x00000034 000 0..011 0100
- 000000000000000000 0000000011 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
38So read block 3
- 000000000000000000 0000000011 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
39No valid data
- 000000000000000000 0000000011 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
0
0
0
0
0
0
0
40Load that cache block, return word f
- 000000000000000000 0000000011 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
1
0
e
f
g
h
0
0
0
0
0
0
41Read 0x00008014 010 0..001 0100
- 000000000000000010 0000000001 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
1
0
e
f
g
h
0
0
0
0
0
0
42So read Cache Block 1, Data is Valid
- 000000000000000010 0000000001 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
1
0
e
f
g
h
0
0
0
0
0
0
43Cache Block 1 Tag does not match (0 ! 2)
- 000000000000000010 0000000001 0100
Tag field
Index field
Offset
Index
0
1
0
a
b
c
d
0
1
0
e
f
g
h
0
0
0
0
0
0
44Miss, so replace block 1 with new data tag
- 000000000000000010 0000000001 0100
Tag field
Index field
Offset
Index
0
1
2
i
j
k
l
0
1
0
e
f
g
h
0
0
0
0
0
0
45And return word j
- 000000000000000010 0000000001 0100
Tag field
Index field
Offset
Index
0
1
2
i
j
k
l
0
1
0
e
f
g
h
0
0
0
0
0
0
46Things to Remember
- We would like to have the capacity of disk at the
speed of the processor unfortunately this is not
feasible. - So we create a memory hierarchy
- each successively lower level contains most
used data from next higher level - Exploit temporal and spatial locality