{"id":477424,"date":"2023-08-09T09:14:50","date_gmt":"2023-08-09T09:14:50","guid":{"rendered":""},"modified":"2023-09-05T11:14:41","modified_gmt":"2023-09-05T11:14:41","slug":"hardware-acceleration","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/hardware-acceleration\/","title":{"rendered":"T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng"},"content":{"rendered":"

T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng \u0111\u1ec1 c\u1eadp \u0111\u1ebfn qu\u00e1 tr\u00ecnh ph\u1ea7n c\u1ee9ng c\u1ee5 th\u1ec3 trong m\u00e1y t\u00ednh, nh\u01b0 GPU (B\u1ed9 x\u1eed l\u00fd \u0111\u1ed3 h\u1ecda), \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 th\u1ef1c hi\u1ec7n m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 nh\u1ea5t \u0111\u1ecbnh hi\u1ec7u qu\u1ea3 h\u01a1n m\u1ee9c c\u00f3 th\u1ec3 trong ph\u1ea7n m\u1ec1m ch\u1ea1y tr\u00ean CPU \u0111a n\u0103ng (B\u1ed9 x\u1eed l\u00fd trung t\u00e2m).<\/p>\n

S\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/h2>\n

Ngu\u1ed3n g\u1ed1c c\u1ee7a kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng b\u1eaft ngu\u1ed3n t\u1eeb nh\u1eefng n\u0103m 1960 v\u00e0 70 v\u1edbi s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a ph\u1ea7n c\u1ee9ng chuy\u00ean d\u1ee5ng cho c\u00e1c t\u00e1c v\u1ee5 nh\u01b0 k\u1ebft xu\u1ea5t \u0111\u1ed3 h\u1ecda trong tr\u00f2 ch\u01a1i \u0111i\u1ec7n t\u1eed v\u00e0 x\u1eed l\u00fd c\u00e1c ph\u00e9p t\u00ednh ph\u1ee9c t\u1ea1p cho nghi\u00ean c\u1ee9u khoa h\u1ecdc. Thu\u1eadt ng\u1eef n\u00e0y l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c \u0111\u1eb7t ra \u0111\u1ec3 ch\u1ec9 vi\u1ec7c s\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng t\u00f9y ch\u1ec9nh \u0111\u1ec3 t\u0103ng t\u1ed1c c\u00e1c ho\u1ea1t \u0111\u1ed9ng ch\u1eadm, t\u1eadn d\u1ee5ng \u0111i\u1ec3m m\u1ea1nh c\u1ee5 th\u1ec3 c\u1ee7a c\u00e1c th\u00e0nh ph\u1ea7n ph\u1ea7n c\u1ee9ng c\u1ee5 th\u1ec3.<\/p>\n

C\u00e1c v\u00ed d\u1ee5 ban \u0111\u1ea7u bao g\u1ed3m card t\u0103ng t\u1ed1c \u0111\u1ed3 h\u1ecda cho PC v\u00e0o nh\u1eefng n\u0103m 1980, l\u00e0 ph\u1ea7n c\u1ee9ng chuy\u00ean d\u1ee5ng \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 th\u1ef1c hi\u1ec7n c\u00e1c t\u00ednh to\u00e1n n\u1eb7ng c\u1ea7n thi\u1ebft \u0111\u1ec3 hi\u1ec3n th\u1ecb \u0111\u1ed3 h\u1ecda 3D. Khi \u0111i\u1ec7n to\u00e1n ph\u00e1t tri\u1ec3n, ph\u1ea7n c\u1ee9ng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 t\u0103ng t\u1ed1c c\u0169ng ph\u00e1t tri\u1ec3n, d\u1eabn \u0111\u1ebfn c\u00e1c th\u00e0nh ph\u1ea7n ti\u00ean ti\u1ebfn ng\u00e0y nay nh\u01b0 GPU, FPGA (M\u1ea3ng c\u1ed5ng l\u1eadp tr\u00ecnh tr\u01b0\u1eddng) v\u00e0 ASICS (M\u1ea1ch t\u00edch h\u1ee3p d\u00e0nh ri\u00eang cho \u1ee9ng d\u1ee5ng).<\/p>\n

S\u1ef1 ph\u1ee9c t\u1ea1p c\u1ee7a vi\u1ec7c t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/h2>\n

T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch gi\u1ea3m t\u1ea3i m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 t\u1ed1n nhi\u1ec1u th\u1eddi gian ho\u1eb7c t\u00ednh to\u00e1n t\u1eeb CPU sang ph\u1ea7n c\u1ee9ng kh\u00e1c c\u00f3 th\u1ec3 th\u1ef1c hi\u1ec7n c\u00e1c t\u00e1c v\u1ee5 n\u00e0y hi\u1ec7u qu\u1ea3 h\u01a1n. \u0110i\u1ec1u n\u00e0y cho ph\u00e9p CPU th\u1ef1c hi\u1ec7n \u0111\u1ed3ng th\u1eddi c\u00e1c t\u00e1c v\u1ee5 kh\u00e1c, gi\u00fap c\u1ea3i thi\u1ec7n hi\u1ec7u su\u1ea5t t\u1ed5ng th\u1ec3 c\u1ee7a h\u1ec7 th\u1ed1ng.<\/p>\n

V\u00ed d\u1ee5: trong k\u1ebft xu\u1ea5t \u0111\u1ed3 h\u1ecda, thay v\u00ec s\u1eed d\u1ee5ng CPU \u0111\u1ec3 t\u00ednh to\u00e1n t\u1eebng pixel trong h\u00ecnh \u1ea3nh, c\u00e1c t\u00e1c v\u1ee5 n\u00e0y c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c g\u1eedi t\u1edbi GPU, \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 x\u1eed l\u00fd vi\u1ec7c x\u1eed l\u00fd s\u1ed1 l\u01b0\u1ee3ng quy m\u00f4 l\u1edbn hi\u1ec7u qu\u1ea3 h\u01a1n. \u0110i\u1ec1u n\u00e0y kh\u00f4ng ch\u1ec9 c\u1ea3i thi\u1ec7n t\u1ed1c \u0111\u1ed9 v\u00e0 hi\u1ec7u su\u1ea5t c\u1ee7a c\u00e1c t\u00e1c v\u1ee5 k\u1ebft xu\u1ea5t m\u00e0 c\u00f2n gi\u00fap CPU r\u1ea3nh r\u1ed7i \u0111\u1ec3 th\u1ef1c hi\u1ec7n c\u00e1c t\u00e1c v\u1ee5 kh\u00e1c.<\/p>\n

C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/h2>\n

M\u1ed9t s\u1ed1 t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng bao g\u1ed3m:<\/p>\n

    \n
  1. \n

    N\u00e2ng cao hi\u1ec7u su\u1ea5t<\/strong>: B\u1eb1ng c\u00e1ch giao nhi\u1ec7m v\u1ee5 cho ph\u1ea7n c\u1ee9ng \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1eb7c bi\u1ec7t \u0111\u1ec3 x\u1eed l\u00fd ch\u00fang, kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng c\u00f3 th\u1ec3 c\u1ea3i thi\u1ec7n \u0111\u00e1ng k\u1ec3 hi\u1ec7u su\u1ea5t c\u1ee7a m\u1ed9t s\u1ed1 \u1ee9ng d\u1ee5ng nh\u1ea5t \u0111\u1ecbnh.<\/p>\n<\/li>\n

  2. \n

    Hi\u1ec7u qu\u1ea3<\/strong>: N\u00f3 mang l\u1ea1i hi\u1ec7u qu\u1ea3 cao h\u01a1n b\u1eb1ng c\u00e1ch cho ph\u00e9p CPU t\u1eadp trung v\u00e0o c\u00e1c t\u00e1c v\u1ee5 kh\u00e1c trong khi ph\u1ea7n c\u1ee9ng c\u1ee5 th\u1ec3 x\u1eed l\u00fd c\u00e1c t\u00e1c v\u1ee5 \u0111\u01b0\u1ee3c ch\u1ec9 \u0111\u1ecbnh.<\/p>\n<\/li>\n

  3. \n

    Gi\u1ea3m m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng<\/strong>: B\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng chuy\u00ean d\u1ee5ng, c\u00e1c t\u00e1c v\u1ee5 c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c ho\u00e0n th\u00e0nh nhanh ch\u00f3ng v\u00e0 hi\u1ec7u qu\u1ea3 h\u01a1n, \u0111i\u1ec1u n\u00e0y c\u00f3 th\u1ec3 gi\u1ea3m m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng t\u1ed5ng th\u1ec3.<\/p>\n<\/li>\n<\/ol>\n

    C\u00e1c lo\u1ea1i t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/h2>\n

    C\u00f3 m\u1ed9t s\u1ed1 lo\u1ea1i t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng, m\u1ed7i lo\u1ea1i li\u00ean quan \u0111\u1ebfn m\u1ed9t lo\u1ea1i ph\u1ea7n c\u1ee9ng kh\u00e1c nhau:<\/p>\n\n\n\n\n\n\n\n\n\n
    Ki\u1ec3u<\/th>\nS\u1ef1 mi\u00eau t\u1ea3<\/th>\n<\/tr>\n<\/thead>\n
    T\u0103ng t\u1ed1c \u0111\u1ed3 h\u1ecda<\/strong><\/td>\nS\u1eed d\u1ee5ng GPU \u0111\u1ec3 hi\u1ec3n th\u1ecb h\u00ecnh \u1ea3nh, ho\u1ea1t \u1ea3nh v\u00e0 video nhanh h\u01a1n v\u00e0 m\u01b0\u1ee3t m\u00e0 h\u01a1n. Th\u01b0\u1eddng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong ch\u01a1i game, k\u1ebft xu\u1ea5t 3D v\u00e0 truy\u1ec1n ph\u00e1t video.<\/td>\n<\/tr>\n
    T\u0103ng t\u1ed1c \u00e2m thanh<\/strong><\/td>\nS\u1eed d\u1ee5ng card \u00e2m thanh ho\u1eb7c b\u1ed9 x\u1eed l\u00fd \u00e2m thanh (APU) \u0111\u1ec3 x\u1eed l\u00fd t\u00edn hi\u1ec7u \u00e2m thanh, gi\u1ea3m t\u1ea3i cho CPU.<\/td>\n<\/tr>\n
    Gia t\u1ed1c v\u1eadt l\u00fd<\/strong><\/td>\nS\u1eed d\u1ee5ng GPU ho\u1eb7c B\u1ed9 x\u1eed l\u00fd v\u1eadt l\u00fd chuy\u00ean d\u1ee5ng (PPU) \u0111\u1ec3 m\u00f4 ph\u1ecfng v\u00e0 t\u00ednh to\u00e1n c\u00e1c h\u00e0nh vi v\u1eadt l\u00fd trong th\u1eddi gian th\u1ef1c, gi\u1ed1ng nh\u01b0 c\u00e1c h\u00e0nh vi \u0111\u01b0\u1ee3c t\u00ecm th\u1ea5y trong tr\u00f2 ch\u01a1i \u0111i\u1ec7n t\u1eed ho\u1eb7c m\u00f4 ph\u1ecfng.<\/td>\n<\/tr>\n
    T\u0103ng t\u1ed1c m\u1ea1ng<\/strong><\/td>\nS\u1eed d\u1ee5ng Th\u1ebb giao di\u1ec7n m\u1ea1ng (NIC) v\u1edbi b\u1ed9 x\u1eed l\u00fd t\u00edch h\u1ee3p \u0111\u1ec3 gi\u1ea3m t\u1ea3i vi\u1ec7c x\u1eed l\u00fd l\u01b0u l\u01b0\u1ee3ng m\u1ea1ng t\u1eeb CPU.<\/td>\n<\/tr>\n
    T\u0103ng t\u1ed1c m\u00e3 h\u00f3a\/gi\u1ea3i m\u00e3<\/strong><\/td>\nS\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng m\u1eadt m\u00e3 chuy\u00ean d\u1ee5ng \u0111\u1ec3 t\u0103ng t\u1ed1c c\u00e1c t\u00e1c v\u1ee5 m\u00e3 h\u00f3a v\u00e0 gi\u1ea3i m\u00e3, h\u1eefu \u00edch trong vi\u1ec7c li\u00ean l\u1ea1c an to\u00e0n.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    S\u1eed d\u1ee5ng t\u00ednh n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng v\u00e0 c\u00e1c th\u00e1ch th\u1ee9c li\u00ean quan<\/h2>\n

    Nhi\u1ec1u \u1ee9ng d\u1ee5ng v\u00e0 h\u1ec7 th\u1ed1ng c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c h\u01b0\u1edfng l\u1ee3i t\u1eeb kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng, bao g\u1ed3m tr\u00f2 ch\u01a1i \u0111i\u1ec7n t\u1eed, n\u1ec1n t\u1ea3ng truy\u1ec1n ph\u00e1t video, m\u00f4 ph\u1ecfng khoa h\u1ecdc v\u00e0 h\u1ec7 th\u1ed1ng li\u00ean l\u1ea1c an to\u00e0n.<\/p>\n

    Tuy nhi\u00ean, vi\u1ec7c s\u1eed d\u1ee5ng kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng c\u0169ng \u0111i k\u00e8m v\u1edbi nh\u1eefng th\u00e1ch th\u1ee9c. M\u1ed9t s\u1ed1 trong s\u1ed1 n\u00e0y bao g\u1ed3m chi ph\u00ed ph\u1ea7n c\u1ee9ng t\u0103ng l\u00ean, nhu c\u1ea7u l\u1eadp tr\u00ecnh chuy\u00ean bi\u1ec7t \u0111\u1ec3 s\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng, c\u00e1c v\u1ea5n \u0111\u1ec1 kh\u00f4ng t\u01b0\u01a1ng th\u00edch ti\u1ec1m \u1ea9n v\u00e0 t\u0103ng m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng cho m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 nh\u1ea5t \u0111\u1ecbnh.<\/p>\n

    Gi\u1ea3i ph\u00e1p cho nh\u1eefng th\u00e1ch th\u1ee9c n\u00e0y c\u00f3 th\u1ec3 bao g\u1ed3m vi\u1ec7c s\u1eed d\u1ee5ng c\u00e1c ti\u00eau chu\u1ea9n m\u1edf v\u00e0 API \u0111\u1ec3 \u0111\u01a1n gi\u1ea3n h\u00f3a vi\u1ec7c l\u1eadp tr\u00ecnh, c\u1ea3i ti\u1ebfn thi\u1ebft k\u1ebf ph\u1ea7n c\u1ee9ng \u0111\u1ec3 gi\u1ea3m m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng v\u00e0 t\u00edch h\u1ee3p t\u1ed1t h\u01a1n gi\u1eefa c\u00e1c th\u00e0nh ph\u1ea7n ph\u1ea7n c\u1ee9ng v\u00e0 ph\u1ea7n m\u1ec1m.<\/p>\n

    So s\u00e1nh v\u1edbi c\u00e1c kh\u00e1i ni\u1ec7m t\u01b0\u01a1ng t\u1ef1<\/h2>\n

    So s\u00e1nh kh\u1ea3 n\u0103ng t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng v\u1edbi \u0111i\u1ec7n to\u00e1n \u0111a n\u0103ng:<\/p>\n\n\n\n\n\n\n\n
    <\/th>\nM\u00e1y t\u00ednh \u0111a n\u0103ng<\/th>\nT\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/th>\n<\/tr>\n<\/thead>\n
    M\u1ee5c \u0111\u00edch<\/strong><\/td>\n\u0110\u01b0\u1ee3c thi\u1ebft k\u1ebf cho nhi\u1ec1u nhi\u1ec7m v\u1ee5 kh\u00e1c nhau<\/td>\n\u0110\u01b0\u1ee3c thi\u1ebft k\u1ebf cho c\u00e1c nhi\u1ec7m v\u1ee5 c\u1ee5 th\u1ec3<\/td>\n<\/tr>\n
    Ph\u1ea7n c\u1ee9ng<\/strong><\/td>\nS\u1eed d\u1ee5ng CPU cho h\u1ea7u h\u1ebft c\u00e1c t\u00e1c v\u1ee5<\/td>\nS\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng c\u1ee5 th\u1ec3 (nh\u01b0 GPU, card \u00e2m thanh, v.v.) cho m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 nh\u1ea5t \u0111\u1ecbnh<\/td>\n<\/tr>\n
    Hi\u1ec7u su\u1ea5t<\/strong><\/td>\nT\u01b0\u01a1ng \u0111\u1ed1i ch\u1eadm h\u01a1n \u0111\u1ed1i v\u1edbi c\u00e1c t\u00e1c v\u1ee5 t\u00ednh to\u00e1n chuy\u00ean s\u00e2u<\/td>\nNhanh h\u01a1n v\u00e0 hi\u1ec7u qu\u1ea3 h\u01a1n cho m\u1ed9t s\u1ed1 nhi\u1ec7m v\u1ee5 nh\u1ea5t \u0111\u1ecbnh<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    T\u01b0\u01a1ng lai c\u1ee7a t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/h2>\n

    Khi c\u00f4ng ngh\u1ec7 ti\u1ebfp t\u1ee5c ph\u00e1t tri\u1ec3n, vai tr\u00f2 c\u1ee7a vi\u1ec7c t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng d\u1ef1 ki\u1ebfn s\u1ebd m\u1edf r\u1ed9ng. Xu h\u01b0\u1edbng s\u1eed d\u1ee5ng c\u00e1c b\u1ed9 t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng d\u00e0nh ri\u00eang cho AI ng\u00e0y c\u00e0ng t\u0103ng \u0111\u1ec3 h\u1ed7 tr\u1ee3 s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a kh\u1ed1i l\u01b0\u1ee3ng c\u00f4ng vi\u1ec7c AI v\u00e0 m\u00e1y h\u1ecdc. Gia t\u1ed1c l\u01b0\u1ee3ng t\u1eed, trong \u0111\u00f3 b\u1ed9 x\u1eed l\u00fd l\u01b0\u1ee3ng t\u1eed \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 t\u0103ng t\u1ed1c c\u00e1c lo\u1ea1i t\u00ednh to\u00e1n c\u1ee5 th\u1ec3, l\u00e0 m\u1ed9t l\u0129nh v\u1ef1c \u0111ang ph\u00e1t tri\u1ec3n kh\u00e1c.<\/p>\n

    T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng v\u00e0 m\u00e1y ch\u1ee7 proxy<\/h2>\n

    T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng c\u0169ng c\u00f3 th\u1ec3 ph\u00f9 h\u1ee3p trong b\u1ed1i c\u1ea3nh m\u00e1y ch\u1ee7 proxy. Trong nh\u1eefng tr\u01b0\u1eddng h\u1ee3p nh\u01b0 v\u1eady, Th\u1ebb giao di\u1ec7n m\u1ea1ng (NIC) c\u00f3 b\u1ed9 x\u1eed l\u00fd t\u00edch h\u1ee3p c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 gi\u1ea3m t\u1ea3i m\u1ed9t s\u1ed1 t\u00e1c v\u1ee5 m\u1ea1ng kh\u1ecfi CPU. \u0110i\u1ec1u n\u00e0y d\u1eabn \u0111\u1ebfn vi\u1ec7c x\u1eed l\u00fd l\u01b0u l\u01b0\u1ee3ng m\u1ea1ng nhanh h\u01a1n v\u00e0 hi\u1ec7u qu\u1ea3 h\u01a1n, c\u00f3 th\u1ec3 mang l\u1ea1i l\u1ee3i \u00edch cho ho\u1ea1t \u0111\u1ed9ng c\u1ee7a m\u00e1y ch\u1ee7 proxy.<\/p>\n

    H\u01a1n n\u1eefa, m\u00e3 h\u00f3a\/gi\u1ea3i m\u00e3 \u0111\u01b0\u1ee3c t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 n\u00e2ng cao hi\u1ec7u su\u1ea5t v\u00e0 t\u00ednh b\u1ea3o m\u1eadt c\u1ee7a m\u00e1y ch\u1ee7 proxy, \u0111\u1eb7c bi\u1ec7t \u0111\u1ed1i v\u1edbi nh\u1eefng m\u00e1y ch\u1ee7 x\u1eed l\u00fd l\u01b0u l\u01b0\u1ee3ng truy c\u1eadp b\u1ea3o m\u1eadt cao.<\/p>\n

    Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n

    \u0110\u1ec3 bi\u1ebft th\u00eam th\u00f4ng tin v\u1ec1 T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng, b\u1ea1n c\u00f3 th\u1ec3 truy c\u1eadp c\u00e1c t\u00e0i nguy\u00ean sau:<\/p>\n

      \n
    1. B\u00e0i vi\u1ebft tr\u00ean Wikipedia v\u1ec1 T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/a><\/li>\n
    2. Gi\u1ea3i th\u00edch c\u1ee7a Microsoft v\u1ec1 t\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng<\/a><\/li>\n
    3. N\u1ec1n t\u1ea3ng t\u0103ng t\u1ed1c h\u1ecdc t\u1eadp s\u00e2u c\u1ee7a NVIDIA<\/a><\/li>\n
    4. T\u0103ng t\u1ed1c ph\u1ea7n c\u1ee9ng c\u1ee7a Intel cho AI v\u00e0 Machine Learning<\/a><\/li>\n<\/ol>","protected":false},"featured_media":477425,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477424","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Hardware Acceleration: Leveraging Hardware to Boost Performance<\/mark>","faq_items":[{"question":"What is Hardware Acceleration?","answer":"

      Hardware acceleration refers to the process where specific hardware in computers, like GPUs (Graphics Processing Units), are used to perform certain tasks more efficiently than is possible in software running on a general-purpose CPU (Central Processing Unit).<\/p>"},{"question":"When did the concept of Hardware Acceleration originate?","answer":"

      The origin of hardware acceleration dates back to the 1960s and 70s with the development of specialized hardware for tasks such as rendering graphics in video games and processing complex calculations for scientific research.<\/p>"},{"question":"How does Hardware Acceleration work?","answer":"

      Hardware acceleration works by offloading some compute-intensive or time-consuming tasks from the CPU to other hardware that can perform these tasks more efficiently. This allows the CPU to perform other tasks concurrently, resulting in overall improved system performance.<\/p>"},{"question":"What are the key features of Hardware Acceleration?","answer":"

      Some of the key features of hardware acceleration include performance enhancement, improved efficiency, and reduced power consumption.<\/p>"},{"question":"What are the different types of Hardware Acceleration?","answer":"

      There are several types of hardware acceleration, including graphics acceleration, sound acceleration, physics acceleration, network acceleration, and encryption\/decryption acceleration.<\/p>"},{"question":"What are some challenges associated with using Hardware Acceleration and how can they be addressed?","answer":"

      Some challenges associated with using hardware acceleration include increased hardware costs, the need for specialized programming, potential incompatibility issues, and increased power consumption for certain tasks. Solutions can include using open standards and APIs, improved hardware design, and better integration between hardware and software components.<\/p>"},{"question":"What are the future perspectives of Hardware Acceleration?","answer":"

      There's a growing trend towards the use of AI-specific hardware accelerators to support the growth of AI and machine learning workloads. Quantum acceleration is another burgeoning field.<\/p>"},{"question":"How can proxy servers use Hardware Acceleration?","answer":"

      Network Interface Cards (NICs) with onboard processors can be used to offload some networking tasks from the CPU, resulting in faster and more efficient network traffic handling for proxy servers. Additionally, hardware-accelerated encryption\/decryption can enhance the performance and security of proxy servers.<\/p>"},{"question":"Where can I find more information about Hardware Acceleration?","answer":"

      You can visit resources like the Wikipedia Article on Hardware Acceleration, Microsoft's Explanation of Hardware Acceleration, NVIDIA\u2019s Deep Learning Acceleration Platform, and Intel's Hardware Acceleration for AI and Machine Learning.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477424","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477424\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/477425"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=477424"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}