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IKI10230 Pengantar Organisasi Komputer Bab 5.2: Cache

IKI10230 Pengantar Organisasi Komputer Bab 5.2: Cache. Sumber : 1. Hamacher. Computer Organization , ed-5. 2. Materi kuliah CS152/1997, UCB. 23 April 2003 Bobby Nazief (nazief@cs.ui.ac.id) Qonita Shahab (niet@cs.ui.ac.id) bahan kuliah: http://www.cs.ui.ac.id/kuliah/iki10230/.

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IKI10230 Pengantar Organisasi Komputer Bab 5.2: Cache

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  1. IKI10230Pengantar Organisasi KomputerBab 5.2: Cache Sumber:1. Hamacher. Computer Organization, ed-5.2. Materi kuliah CS152/1997, UCB. 23 April 2003 Bobby Nazief (nazief@cs.ui.ac.id)Qonita Shahab (niet@cs.ui.ac.id) bahan kuliah: http://www.cs.ui.ac.id/kuliah/iki10230/

  2. MEMORY HIERARCHY

  3. Memory Hierarchy (1/4) • Prosesor • menjalankan program • sangat cepat waktu eksekusi dalam orde nanoseconds sampai dengan picoseconds • perlu mengakses kode dan data program!Dimana program berada? • Disk • HUGE capacity (virtually limitless) • VERY slow: runs on order of milliseconds • so how do we account for this gap?  Menggunakan teknologi memori!

  4. Memory Hierarchy (2/4) • Memory (DRAM) • Kapasitas jauh lebih besar dari registers, lebih kecil dari disk (tetap terbatas) • Access time ~50-100 nano-detik, jauh lebih cepat dari disk (mili-detik) • Mengandung subset data pada disk (basically portions of programs that are currently being run) • Fakta: memori dengan kapasitas besar (murah!) lambat, sedangkan memori dengan kapasitas kecil (mahal) cepat. • Solution: bagaimana menyediakan (ilusi) kapasitas besar dan akses cepat!

  5. Processor Increasing Distance from Proc.,Decreasing cost / MB Levels in memory hierarchy Level 1 Level 2 Level 3 . . . Level n Size of memory at each level Memory Hierarchy (3/4) Higher Lower

  6. Memory Hierarchy (4/4) • Pada tingkat yang lebih dekat dengan Prosesor, mempunyai karakteristik: • Lebih kecil, • Lebih cepat, • Subset semua data pada level lebih atas (mis. menyimpan data yang sering digunakan) • Efisien dalam pemilihan mana data yang akan disimpan, karena tempat terbatas • Lowest Level (usually disk) contains all available data

  7. Memory Hierarchy Analogy: Library (1/2) • You’re writing a term paper (Processor) at a table in Doe • Doe 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 you’ve already retrieved it

  8. Memory Hierarchy Analogy: Library (2/2) • 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

  9. Probability of reference 0 2^n - 1 Address Space Why hierarchy works • The Principle of Locality: • Program access a relatively small portion of the address space at any instant of time.

  10. Lower Level Memory Upper Level Memory To Processor Blk X From Processor Blk Y Memory Hierarchy: How Does it Work? • Temporal Locality (Locality in Time):  Keep most recently accessed data items closer to the processor • Spatial Locality (Locality in Space):  Move blocks consists of contiguous words to the upper levels

  11. Processor Control Tertiary Storage (Disk) Secondary Storage (Disk) Second Level Cache (SRAM) Main Memory (DRAM) On-Chip Cache Datapath Registers Speed (ns): 1s 10s 100s 10,000,000s (10s ms) 10,000,000,000s (10s sec) Size (bytes): 100s Ks Ms Gs Ts Modern Computer System • 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.

  12. How is the hierarchy managed? • Registers <-> Memory • by compiler (programmer?) • Cache <-> Memory • by the hardware • Memory <-> Disks • by the hardware and operating system (virtual memory) • by the programmer (files)

  13. Basis of Memory Hierarchy • 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, we’ll want to use it again soon

  14. Cache

  15. Processor Reg Cache Memory-I/O bus I/O controller I/O controller I/O controller Memory Display Network disk disk Disk Disk Organisasi Hierarki Memori: Cache

  16. What is a cache? • Kecil, storage cepat untuk meningkatkan “average access time” dibandingkan memori • Memanfaatkan spatial & temporal locality • Sebenarnya “cache” terlihat pada hirarkis penyimpanan • Registers “a cache” on variables – software managed • First-level cache a cache on second-level cache • Second-level cache a cache on memory • Memory a cache on disk (virtual memory)

  17. Cache Design • Bagaimana organisasi cache? (ingat: cache akan menerima alamat memori dari prosesor, tidak ada perubahan pada rancangan prosesor ada/tanpa cache). • Bagaimana melakukan mapping (relasi) antara alamat memori dengan cache (ingat: prosesor hanya melihat memory byte addressable) • Bagaimana mengetahui elemen data tsb berada di cache (hit) atau tidak ada (miss) (ingat: cache jauh lebih kecil dari main memory)?

  18. MainMemory Cache To Processor Blk X From Processor Blk Y Cache: Blok Memory • Transfer data antara cache dan memori dalam satuan blok (kelipatan words) • Mapping (penerjemahan) antara blok di cache dan di main memory (ingat: cache copy dari main memory) Hit

  19. 4 Byte Direct Mapped Cache Cache Index Memory Address Memory 0 0 1 1 2 2 3 3 4 5 6 7 8 9 A B C D E F Direct Mapping • Lokasi cache 0 dapat diisidata lokasi dari: • Lokasi memori:0, 4, 8, ... • Secara umum: lokasi memori yang merupakan kelipatan 4 (jumlah blok cache)

  20. 4 Byte Associative Mapped Cache Cache Index Memory Address Memory 0 0 1 1 2 2 3 3 4 5 6 7 8 9 A B C D E F Associative Mapping

  21. 4 Byte Set-Associative Mapped Cache Cache Index Memory Address Memory 0 0 0 1 1 2 2 1 3 3 4 Cache Set 5 6 7 8 9 A B C D E F Set-Associative Mapping

  22. Address Mapping

  23. tttttttttttttttttiiiiiiiiiioooo tagindexbyte to checktooffsetif haveselectwithincorrect blockblockblock Example: Direct-Mapped • Masalah: multiple alamat memori “map” ke indeks blok yang sama! • Bagaimana kita mengetahui apakah alamat blok yang diinginkan berada di cache? • Harus ada identifikasi blok memori dikaitkan dengan alamat • Bagaimana jika ukuran blok > 1 byte? • Solusi: bagi alamat dalam bentuk fields

  24. Cache Address Terminology • Semua fields untuk penerjemahan dianggap sebagai bilangan positif integer. • Index: indeks pada blok cache, dimana blok (baris, entry) dari cache alamat tersebut harus berada. • Offset: sekali kita telah menemukan blok tsb, manakah byte pada blok tersebut akan diakses. • Tag: sisa bit dari alamat setelah field index dan offset; digunakan untuk membedakan alamat memory yang mappingnya pada blok yang sama dari cache.

  25. Direct-Mapped Cache Example (1/3) • Misalkan kita mempunya 16KB data dengan skema direct-mapped cache. • Setiap blok terdiri dari 4 word • Tentukan ukuran field: tag, index, dan offset jika menggunakan komputer 32-bit. • Offset • Diperlukan untuk mengambil satu byte dalam blok • blok mempunyai: 4 words 16 bytes 24 bytes • diperlukan 4 bit untuk menentukan alamat byte

  26. Direct-Mapped Cache Example (2/3) • Index: (~index into an “array of blocks”) • diperlukan untuk menentukan blok yang mana pada cache (rows yang mana) • cache mempunyai 16 KB = 214 bytes • blok mempunyai 24 bytes (4 words) # rows/cache = # blocks/cache (sebab setiap rows terdiri dari satu blok) = bytes/cache / bytes/row = 214 bytes/cache / 24 bytes/row = 210 rows/cache • diperlukan 10 bit untuk menentukan indeks pada rows dari cache • Tag: 32 – (4 + 10) = 18 bit

  27. Direct-Mapped Cache Example (3/3) • Contoh direct mapped cache tsb membagi field atas • 4 bits offset • 10 bit index • 18 bit tag • Struktur cache: • Menyimpan tag (unik untuk setiap blok) dikaitkan dengan blok/rows. • Akses dilakukan dengan mencari index blok/ rows • Bandingkan tag dari alamat dan tag yang disimpan pada row tersebut • Jika tag sama => HIT, ambil byte (offset) • Jika tidak sama => MISS, ambil blok dari memori.

  28. Cache Index 0000000000 0000000001 0000000010 tttttttttttttttttiiiiiiiiiioooo 0000000011 Akses Memori pada Direct-mapped Cache Cache Tag 000000000000000000

  29. Replacement Algorithms • Berlaku bagi: • Associative Mapping • Set-Associative Mapping • Bagaimana menempatkan blok baru jika cache sudah penuh  berpengaruh pada kinerja! • Beberapa algoritme: • LRU: Least Recently Used • LFU: Least Frequently Used • Random

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