ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

VI. 㧗ᛶ⬟ィ⟬ࢩࢫࢸ࣒◊✲✲㒊㛛
1.

࣓ࣥࣂ࣮

ᩍᤵ బ⸨ ୕ஂࠊᮔ Ὀ♸ࠊඣ⋢ ♸ᝋࠊ㧗ᶫ ኱௓෸ᩍᤵ ᘓ㒊 ಟぢࠊሮ ᩄ༤ຓᩍ ከ⏣㔝 ᐶே◊✲ဨ ⏣୰ ᫀᏹࠊ㎷ ⨾࿴Ꮚࠊᱵ⏣ ᏹ᫂ࠊ୰ᑿ ᫀᗈࠊያ㈡ ⚽⏨
㻌
2.

ᴫせ

ᮏ◊✲㒊㛛࡛ࡣࠊ㧗ᛶ⬟ィ⟬ࢩࢫࢸ࣒࢔࣮࢟ࢸࢡࢳࣕࠊ୪ิࣉࣟࢢ࣑ࣛࣥࢢ⎔ቃࠊ㻳㻼㼁฼⏝ᢏ⾡ࠊ୪ิᩘ್ฎ⌮ࡢ㧗㏿໬◊✲ࠊᗈᇦศᩓ⎔ቃ࡟࠾ࡅࡿࢹ࣮ࢱඹ᭷ࢆ୰ᚰ࡜ࡍࡿ
ࢢࣜࢵࢻィ⟬ᢏ⾡➼ࡢ◊✲ࢆ⾜ࡗ࡚࠸ࡿࠋ㻌
㻌
3.

◊✲ᡂᯝ

࠙₇⟬ຍ㏿ᶵᵓࢆᣢࡘᑗ᮶ࡢ HPCI ࢩࢫࢸ࣒࡟㛵ࡍࡿㄪᰝ◊✲ࠚ㸦బ⸨ࠊᮔࠊඣ⋢ࠊ㧗ᶫ㸧ᮏㄪᰝ◊✲࡟࠾࠸࡚ࡣࠊᑗ᮶ࡢ HPCI ࢩࢫࢸ࣒ࡢ࠶ࡾ᪉ࡢㄪᰝ◊✲࡟ᑐࡋ࡚⛉Ꮫᢏ⾡ィ⟬ࡢ࢔ࣉࣜࢣ࣮ࢩࣙࣥ࡟㐺ྜࡋࡓ₇⟬ຍ㏿ᶵᵓ࡟ࡼࡿ୪ิ኱つᶍࢩࢫࢸ࣒ࢆᥦ᱌ࡋࠊㄪ
ᰝ◊✲ࢆ⾜ࡗࡓࠋ ⌧ᅾࡢ᭱ඛ➃ࡢࢫࣃࢥࣥࡣ኱つᶍ࡞୪ิࢩࢫࢸ࣒࡛࠶ࡾࠊಶࠎࡢせ⣲࡛࠶ࡿࣉࣟࢭࢵ
ࢧࡢ㧗ᛶ⬟໬࡜࡜ࡶ࡟ࠊࢩࢫࢸ࣒ࢆᵓᡂࡍࡿࣉࣟࢭࢵࢧᩘࢆቑࡸࡍࡇ࡜࡟ࡼࡾ㧗ᛶ⬟໬ࢆ㐩ᡂࡋ࡚ࡁࡓࠋࢼࣀࢸࢡࡸࣛ࢖ࣇࢧ࢖࢚ࣥࢫࡢ㐍ṌࠊẼೃẼ㇟ணࡸᆅ㟈࣭㜵⅏࡬ࡢᑐฎ࡟ࡣィ⟬⛉Ꮫࡣ୙ྍḞ࠿ࡘ᭷ຠ࡞ᡭẁ࡛࠶ࡾࠊࡑࡢ௚ࡢᵝࠎ࡞ィ⟬⛉Ꮫࡢㅖศ㔝࡟࠾࠸࡚ࠊࡑࡢࡓࡵ࡟ࡣࡉࡽ࡞ࡿィ⟬⬟ຊࡀせㄳࡉࢀ࡚࠸ࡿࠋࡋ࠿ࡋࠊᛶ⬟ࡢࡉࡽ࡞ࡿྥ
ୖࡢࡓࡵ࡟ࣉࣟࢭࢵࢧᩘࢆࡉࡽ࡟ቑࡸࡍࠊࡇࢀࡲ࡛ࡢ࢔ࣉ࣮ࣟࢳࡣタ⨨㠃✚ࠊᾘ㈝㟁ຊ➼ࡢไ㝈࠿ࡽࠊ㝈⏺ࡀぢ࠼࡚ࡁࡓࠋࡉࡽ࡟ᛶ⬟ࢆྥୖࡉࡏࡿࡓࡵ࡟ࡣࠊ₇⟬ᛶ⬟ࢆ㔜どࡋࡓࣉࣟࢭࢵࢧᵓᡂࡸࠊࢳࢵࣉෆ࣓ࣔࣜ࡟ࡼࡿࣂࣥࢻᖜࡢྥୖࠊ≉ᐃ࢔ࣉࣜࢣ࣮ࢩࣙࣥ
࡟≉໬ࡋࡓ₇⟬ᅇ㊰࡞࡝ࢆᑟධࡍࡿࡇ࡜࡟ࡼࡾࠊỗ⏝ⓗ࡞ฎ⌮ࢆ⾜࠺ᚑ᮶ࡢỗ⏝ࣉࣟࢭࢵࢧࡼࡾࡶ኱ᖜ࡞ฎ⌮ᛶ⬟ࡢྥୖ࡜㟁ຊຠ⋡ࡢᨵၿࡀᚲせ࡛࠶ࡿࠋࡉࡽ࡟ࠊࣛ࢖ࣇࢧ࢖
࢚ࣥࢫࡢศᏊࢩ࣑࣮ࣗࣞࢩࣙࣥ࡞࡝ࠊከࡃࡢ࢔ࣉࣜ࡟࠾࠸୍࡚ᐃࡢၥ㢟ࡢ㧗㏿໬㸦ᙉࢫࢣ࣮ࣜࣥࢢ㸧ࡀせㄳࡉࢀࡿࡼ࠺࡟࡞ࡗ࡚ࡁࡓࠋᮏㄪᰝ◊✲࡛ࡣࠊࡇࡢࡼ࠺࡞㟁ຊຠ⋡ࡢ኱ᖜ࡞ຠ⋡໬࡜ᙉࢫࢣ࣮ࣜࣥࢢ࡟ࡼࡿ᪂ࡓ࡞ィ⟬⛉Ꮫࡢᒎ㛤ࢆ┠ᣦࡋ࡚ࠊ₇⟬ຍ㏿ᶵᵓ࡟ࡼࡿ୪ิ኱つᶍࢩࢫࢸ࣒࡟ࡘ࠸࡚ㄪᰝ◊✲ࢆ⾜ࡗ࡚࠸ࡿࠋ ᮏㄪᰝ◊✲࡟᝿ᐃࡍࡿࢩࢫࢸ࣒࡟ࡘ࠸࡚ࡢᴫ␎࡟ࡘ࠸࡚ᅗ 1 ࡟♧ࡍࠋከᩘࡢ₇⟬ࢥ࢔ࢆෆⶶࡋࡓࢳࢵࣉ࡟ࡼࡿ₇⟬ຍ㏿ᶵᵓࡀỗ⏝ࣉࣟࢭࢵࢧ࡛ᵓᡂࡉࢀࡓ୪ิࢩࢫࢸ࣒ࡢ
ྛࣀ࣮ࢻ࡟᥋⥆ࡶࡋࡃࡣෆⶶࡉࢀ࡚࠸ࡿ࣊ࢸࣟࢪ࣮ࢽ࢔ࢫ࡞୪ิࢩࢫࢸ࣒ࢆ᝿ᐃࡍࡿࠋ
146

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

₇⟬ຍ㏿ᶵᵓࡣࠊከᩘࡢࢫ࣮ࣝࣉࢵࢺࢥ࢔࡟ࡼࡾᵓᡂࡉࢀࠊࢳࢵࣉෆࢿࢵࢺ࣮࣡ࢡ࡟ࡼ
ࡾ⤖ྜࡉࢀࡿࠋࢥ࢔ࡣ࣮࣓ࣟ࢝ࣝࣔࣜࢆᣢࡕࠊ࣓ࢵࢩࣗࢿࢵࢺ࣮࣡ࢡ࡛⤖ྜࡉࢀࡿࠋ࠸
ࡃࡘ࠿ࡢࢥ࢔ࡈ࡜࡟ࢥࣥࢺ࣮࡛ࣟࣛྠᮇไᚚ㸦SIMD㸧ࡉࢀࡿࠋᙜヱᖺᗘ࡟࠾࠸࡚ࡣࠊྛศ㔝࠿ࡽࡢ࢔ࣉࣜࢆㄪᰝࡋࠊCo-design ࡟ࡼࡾᇶᮏ࢔࣮࢟ࢸࢡ
ࢳࣕࢆ᳨ウࡋࡓࠋᅗ  ㄪᰝ◊✲ࡢᑐ㇟࡜ࡍࡿࢩࢫࢸ࣒ࡢ᝿ᐃᴫ␎

࠙ḟୡ௦୪ิฎ⌮ゝㄒ XcalableMP ࡢ◊✲㛤Ⓨࠚ㸦బ⸨㸧 E-Science ࣉࣟࢪ࢙ࢡࢺࠕ୪ิࣉࣟࢢ࣑ࣛࣥࢢゝㄒ࡟㛵ࡍࡿ◊✲㛤Ⓨ ࠖ࡟࠾࠸࡚㛤Ⓨࢆ㐍ࡵࡓࠊศᩓ࣓ࣔࣜᵓᡂࢆᇶᮏ࡜ࡍࡿ኱つᶍ୪ิฎ⌮ࢩࢫࢸ࣒࡟࠾ࡅࡿ୪ิ HPC
࢔ࣉࣜࢣ࣮ࢩࣙࣥࡢࡓࡵࠊ୪ิࣉࣟࢢ࣑ࣛࣥࢢゝㄒ XcalableMP㸦XMP㸧ࡢ㛤Ⓨ࣭ᨵၿࢆᘬࡁ⥆ࡁ⾜ࡗ࡚࠸ࡿࠋᶆ‽໬ࡢάືࢆ PC ࢡࣛࢫࢱࢥࣥࢯ࣮ࢩ࢔࣒ࡢ XMP つ᱁㒊఍ࢆタ⨨ࡋࠊ⾜ࡗ࡚࠸ࡿࠋᙜヱᖺᗘ࡟࠾࠸࡚ࡣࠊ1.0 ࢆᨵၿࡋࡓࠊXMP Version 1.1 ࢆබ㛤ࡋࡓࠋࡇࢀࡲ࡛ࡢ C ゝㄒ࡟ຍ࠼࡚ࠊFortran95 ࡢ XMP ࢥࣥࣃ࢖ࣛࢆ⾜࠸බ㛤ࡋࡓࠋ
 XMP version 1.1 ࡢ௙ᵝཬࡧࣉࣟࢺࢱ࢖ࣉࢥࣥࣃ࢖ࣛ࡟ࡘ࠸࡚ࡣࠊࡑࢀࡒࢀ௨ୗࡢ
URL ࡟࠾࠸࡚බ㛤ࡉࢀ࡚࠸ࡿࠋ   ;03YHUVLRQ௙ᵝ㸸 KWWSZZZ[FDODEOHPSRUJVSHF[PSVSHFSGI   ࣉࣟࢺࢱ࢖ࣉࢥࣥࣃ࢖ࣛ㸸KWWSZZZ[FDODEOHPSRUJGRZQORDGKWPO147

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

࠙HA-PACS/TCA ࡢ◊✲㛤Ⓨࠚ㸦ᮔࠊඣ⋢ࠊሮ㸧 ᩥ㒊⛉Ꮫ┬≉ู⤒㈝ࠕ࢚ࢡࢧࢫࢣ࣮ࣝィ⟬ᢏ⾡㛤ᣅ࡟ࡼࡿඛ➃Ꮫ㝿ィ⟬⛉Ꮫᩍ⫱◊✲ᣐⅬࡢ඘ᐇࠖ㸦H23ࠥH25 ᖺᗘࡢ 3 ᖺ㛫㸧࡟࠾࠸࡚ࠊᐦ⤖ྜ₇⟬ຍ㏿⿦⨨㸦Tightly
Coupled Accelerators: TCA㸧ࢆᥦ᱌ࡋࠊ୰᰾࡜࡞ࡿ PEACH2 (PCI Express Adaptive
Communication Hub ver.2)ࢳࢵࣉࢆ FPGA ࡟ࡼࡾᐇ⿦ࡋࠊࡇࢀࢆỗ⏝ GPU ࢡࣛࢫࢱࣀ࣮ࢻ࡟ᐇ⿦ࡍࡿࡓࡵࡢ PCI Express ࣮࣎ࢻࢆ㛤Ⓨࡋ࡚࠸ࡿࠋ๓ᖺᗘ࡟⾜ࡗࡓࣉࣟࢺ
ࢱ࢖ࣉࣁ࣮ࢻ࢙࢘࢔ࡢᐇ⿦࡟ᇶ࡙ࡁࠊ௒ᖺᗘࡣ PEACH2 ࣮࣎ࢻࡢ㔞⏘࡜ࠊFPGA ୖࡢᅇ㊰࡟ PEACH2 ࡢᇶᮏⓗ࡞ᶵ⬟ࢆᐇ⿦ࡋࠊ8 ࣀ࣮ࢻࡢᐇ㦂ࢩࢫࢸ࣒ୖ࡛ࡢືస☜ㄆࢆ⾜ࡗࡓࠋࡲࡓࠊึᮇⓗ࡞㏻ಙᛶ⬟ホ౯ཬࡧᶵ⬟☜ㄆࢆ⾜ࡗࡓࠋࡇࢀࡽ࡟ࡼࡾࠊTCA ࡢ
GPU ࢡࣛࢫࢱᐇ⿦࡟࠾࠸࡚ᚲせ࡜ࡉࢀࡿᇶᮏᶵ⬟ࡀᐇ⌧ࡉࢀ࡚࠸ࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋᅗ PEACH2 ࣮࣎ࢻ㸦㔞⏘ᆺ㸧 PEACH2 ࣮࣎ࢻࡢ㔞⏘ࢱ࢖ࣉࡣࠊࣉࣟࢺࢱ࢖ࣉ࡜ᇶᮏⓗ࡟ྠࡌᵓᡂࢆᣢࡕࠊAltera♫〇 Stratix IV GX ࢆ⏝࠸ࠊྠ♫ࡀᥦ౪ࡍࡿ PCI Express gen.2 IP ࢆ 4 ࣏࣮ࢺ㸦ྛ࣏࣮ࢺ x8 lane㸧ᐇ⿦ࡋ࡚࠸ࡿࠋࡇࡢ௚ࠊFPGA ෆ࡟ࡣỗ⏝ CPU ࢥ࢔ࠊDMA ࢥࣥࢺ࣮ࣟ
ࣛ➼ࢆ⤌ࡳ㎸ࡳࠊTCA ࢔࣮࢟ࢸࢡࢳࣕ࡟ᇶ࡙ࡃ GPU 㛫┤᥋㏻ಙ࡟࠾ࡅࡿపࣞ࢖ࢸࣥࢩ
㏻ಙ࡜ከᵝ࡞ HPC ࢔ࣉࣜࢣ࣮ࢩࣙࣥ࡟ᑐᛂࡍࡿᇶᮏᶵ⬟ࢆഛ࠼࡚࠸ࡿࠋᅗ 2 ࡟
PEACH2 㔞⏘࣮࣎ࢻࡢ෗┿ࢆ♧ࡍࠋ ࡇࡢ࣮࣎ࢻࢆ HA-PACS ࣮࣋ࢫࢡࣛࢫࢱ࡜ྠ➼ࡢᵓᡂࢆᣢࡘィ⟬ࢧ࣮ࣂ࡟⿦╔ࡋࠊ2
ࣀ࣮ࢻ࡟㊬ࡿ㏻ಙᛶ⬟ࢆᐃࡋࡓ⤖ᯝࢆᅗ 3 ࡟♧ࡍࠋࣂࣥࢻᖜ࡟ࡘ࠸࡚ࡣࠊࣁ࣮ࢻ࢘

࢙࢔࡜ࡋ࡚ࡢ PCI Express gen.2 x8 lane ࡢ⌮ㄽࣆ࣮ࢡᛶ⬟ࡢ 95%ࡀฟ࡚࠾ࡾࠊࣞ࢖ࢸ
ࣥࢩ࡜ࡋ࡚ࡣ CPU ࠿ࡽࡢ㏻ಙࡢሙྜ࡟᭱ᑠ್࡛⣙ 1ȣ⛊ࡀ㐩ᡂࡉࢀ࡚࠸ࡿࠋࡓࡔࡋࠊ
⌧᫬Ⅼ࡛౑⏝ࡋ࡚࠸ࡿ Intel SandyBridge E5 ࡢࣉࣟࢭࢵࢧ࡛ࡣࠊPCI Express ࣂࢫୖࡢࢹࣂ࢖ࢫ㛫㏻ಙ࡟ࣁ࣮ࢻ࢙࢘࢔ⓗ࣎ࢺࣝࢿࢵࢡࡀ࠶ࡾࠊ
ࣀ࣮ࢻ㛫 GPU 㛫㌿㏦࡛ࡣ 2.5
ȣ⛊⛬ᗘࡀࣞ࢖ࢸࣥࢩࡢ㝈⏺࡛࠶ࡿࠋࡇࢀࡣ PEACH2 ⮬యࡢᮏ㉁ⓗ࡞ᛶ⬟࡛ࡣ࡞ࡃ
㸦CPU ࢆ௓ࡋࡓ㏻ಙ࡛ࡣࣞ࢖ࢸࣥࢩࡣࡇࡢ༙ศ௨ୗ㸧
ࠊCPU ࡢ PCI Express ࡢၥ㢟࡛࠶ࡾࠊ௒ᚋࡢ CPU ࡢᨵⰋ࡟ࡼࡾᨵၿࡉࢀ࡚࠸ࡃࡶࡢ࡜ᛮࢃࢀࡿࠋ
148

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩࠙㉸୪ิ GPU ࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢᢏ⾡࡟㛵ࡍࡿ◊✲ࠚ㸦బ⸨ࠊᮔ㸧 ᡓ␎ⓗᅜ㝿⛉Ꮫᢏ⾡༠ຊ᥎㐍஦ᴗ㸦᪥௖ඹྠ◊✲㸧ࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝࢥࣥࣆ࣮ࣗ
ࢸ࢕ࣥࢢࡢࡓࡵࡢࣇ࣮࣒࣮ࣞ࣡ࢡ࡜ࣉࣟࢢ࣑ࣛࣥࢢࠖ࡟࠾࠸࡚ࠊ㉸୪ิ *38 ࢡࣛࢫࢱ࡟
࠾ࡅࡿ୪ิࣉࣟࢢ࣑ࣛࣥࢢ⎔ቃ࡟㛵ࡍࡿ◊✲ࢆ⾜ࡗ࡚࠸ࡿࠋᙜヱᖺᗘ࡟࠾࠸࡚ࡣࠊࣇࣛ
ࣥࢫഃࡀ㛤Ⓨࡋࡓ࢔ࣝࢦࣜࢬ࣒グ㏙⏝ࡢࣇ࣮ࣟゝㄒ <0/ ࡜ࡢ⤫ྜࢆ⾜ࡗࡓࠋᚑ᮶ࡢ <0/࡛ࡣࠊࣇ࣮ࣟࡢ୰࡛⏝࠸ࡿࡇ࡜ࡀ࡛ࡁࡿィ⟬ࢥ࣏࣮ࣥࢿࣥࢺࡀ㏲ḟࣉࣟࢢ࣒ࣛࡔࡅࡔࡗ
ࡓࡀࠊ;03 ࡛グ㏙ࡉࢀࡓᅗ PEACH2 ࣮࣎ࢻ࡟ࡼࡿ CPU 㛫ཬࡧ GPU 㛫㏻ಙᛶ⬟㸦ᕥ㸸ࣞ࢖ࢸࣥࢩࠊྑ㸸ࣂࣥࢻᖜ㸧」ᩘࣉࣟࢭࢫࡢࢥ࣏࣮ࣥࢿࣥࢺࡀసᡂ࡛ࡁࡿࠋ<0/ ࡣࠊᡃࠎࡀ㛤Ⓨࡋࡓ 2PQL53& ࢆᐇ⾜᫬ࡢࢫࢣࢪ࣮ࣗࣛ࡜ࡋ࡚౑ࡗ࡚࠸ࡿࠋࡇࡢᣑᙇࢆ⾜࠺ࡓࡵ࡟ 2PQL53& ࢆᨵ㐀ࡋ࡚⾜ࡗࡓࠋࡇࢀ࡟ࡼࡾࠊ030' 0XOWLSOH3URJUDP0XOWLSOH'DWD ࡢ᪂ࡋ࠸ࣉࣟࢢ࣑ࣛࣥࢢࣔࢹࣝࢆᥦ
せࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡇࢀࢆࠊࣈࣟࢵࢡᆺࡢ࢞࢘ࢫࢪࣙࣝࢲࣥἲࡢࣉࣟࢢ࣒ࣛࢆసᡂࡋࠊ
ࡑࡢ᭷ຠᛶࢆ☜ㄆࡋࡓࠋ ࡲࡓࠊ*38 ࡜ేࡏ࡚㧗ᛶ⬟໬࣭ࢥ࢔ᩘቑ኱ࡀ㐍ࡴ &38 ᛶ⬟࡟╔┠ࡋࠊ༢୍࣮ࣝࣉෆࡢ
ከᩘࡢィ⟬ࢆྛࣀ࣮ࢻୖࡢ *38 ࡜ &38 ࡟๭ࡾᙜ࡚ࠊࣀ࣮ࢻୖࡢィ⟬ࣜࢯ࣮ࢫࢆ᭱኱㝈฼⏝ࡍࡿ࢔ࣉ࣮ࣟࢳ࡜ࡋ࡚ࠊ;03 ࡢ *38 ᑐᛂ∧࡛࠶ࡿ ;03GHY ࡟ *38&38 ࣮࣡ࢡࢩ࢙࢔ࣜ
ࣥࢢᶵ⬟ࢆ㏣ຍࡋࡓ ;03GHY6WDU38 ࢆ㛤Ⓨࡋ࡚࠸ࡿࠋࡇࢀࡣࣇࣛࣥࢫ ,15,$ ࡟࠾࠸࡚㛤Ⓨࡉࢀ࡚࠸ࡿ 6WDU38 ࢫࢣࢪ࣮ࣗࣛ࡜ ;03 ࢥࣥࣃ࢖ࣛࢆ⤌ࡳྜࢃࡏࡿᙧ࡛ᐇ⌧ࡉࢀࡿඹྠ◊✲࡛࠶ࡿࠋ௒ᖺᗘࡢ◊✲࡛ࡣࠊ*38 ࡜ &38 ࢥ࢔ࡢᛶ⬟ᕪࡀ኱ࡁ࠸Ⅼ࡟ὀ┠ࡋࠊ࣮ࣝࣉ୰ࡢࢱࢫࢡࢆ༢࡟ࢱࢫࢡᩘ࡛ศ๭ࡍࡿࡢ࡛ࡣ࡞ࡃࠊ๭ࡾᙜ࡚ࡿࢱࢫࢡࢧ࢖ࢬࡑࡢࡶ
ࡢࢆࠊࣜࢯ࣮ࢫࡢᛶ⬟࡟ྜࢃࡏ࡚᭱㐺໬ࡋࠊ㐺ᗘ࡞࣮ࣟࢻࣂࣛࣥࢫࢆྲྀࡿࡇ࡜࡟ࡼࡾࠊ
*38 ࡢࡳࢆ฼⏝ࡋࡓሙྜ࡟ẚ࡭ᛶ⬟ྥୖࡀᚓࡽࢀࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋ⾜ิ✚ィ⟬ࡸከయၥ㢟ࢆ +$3$&6 ࣮࣋ࢫࢡࣛࢫࢱୖࡢ ;03GHY6WDU38 ࣉࣟࢺࢱ࢖ࣉࢥࣥࣃ࢖࡛ࣛホ౯ࡋࠊ149

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩*38 ࡢࡳࡢሙྜ࡟ẚ࡭ ࠥ ಸ⛬ᗘࡲ࡛ᛶ⬟ࡀྥୖࡍࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋ࠙኱つᶍᗈᇦศᩓࣇ࢓࢖ࣝࢩࢫࢸ࣒ཬࡧࢢࣜࢵࢻ㸭ࢡࣛ࢘ࢻᢏ⾡࡟㛵ࡍࡿ◊✲ࠚ㸦ᘓ㒊㸧 ᩥ㒊⛉Ꮫ┬ࡀ㐍ࡵࡿ㠉᪂ⓗࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ࢖ࣥࣇࣛ㸦HPCI㸧ࡢ HPCI ඹ⏝ࢫࢺ࣮ࣞࢪࡢࢩࢫࢸ࣒ࢯࣇࢺ࢙࢘࢔࡜ࡋ࡚฼⏝ࡉࢀࡿ Gfarm ࣇ࢓࢖ࣝࢩ
ࢫࢸ࣒ࡢᩚഛࢆ⾜ࡗࡓࠋලయⓗ࡟ࡣࠊ㧗㈇Ⲵヨ㦂ࠊ୙ලྜಟṇࠊࣇ࢓࢖ࣝ」〇ᩘࡢ⮬ືಖᣢࠊ୍㈏ᛶࢳ࢙ࢵࢡࡢ㧗㏿໬ࠊ㐠⏝┘どࢩࢫࢸ࣒ࠊᛶ⬟┘どࢩࢫࢸ࣒ࠊࢻ࣓࢟ࣗࣥࢺ
ࡢ᭦᪂ࠊࣇ࢓࢖ࣝ」〇㓄⨨ࡢࢢ࣮ࣝࣉᣦᐃ࡞࡝࡛࠶ࡿࠋࡇࡢ⤖ᯝ࡜ࡋ࡚ࠊGfarm ࣂ࣮ࢪࣙࣥ 2.5.8 ࢆ࣮ࣜࣜࢫࡋࡓࠋࡑࡢᡂᯝࢆࠊ㐠⏝୰ࡢ QCD ࢹ࣮ࢱඹ᭷ࢩࢫࢸ࣒ࡢ JLDG࡛ά⏝ࡍࡿࡓࡵࡢ‽ഛࢆࡍࡍࡵࡓࠋ
㻌࠙㧗ᛶ⬟୪ิᩘ್ィ⟬࡟㛵ࡍࡿ◊✲ࠚ(1) ୪ิ㧗㏿ࣇ࣮࢚ࣜኚ᥮㸦FFT㸧ࡢ㧗㏿໬ᡭἲ࡟㛵ࡍࡿ◊✲㸦㧗ᶫ㸧⛉Ꮫᢏ⾡ィ⟬࡛ᗈࡃ⏝࠸ࡽࢀ࡚࠸ࡿ୪ิ㧗㏿ࣇ࣮࢚ࣜኚ᥮㸦FFT㸧ࡢᛶ⬟ࢆᨵၿࡍࡿ
ࡓࡵ࡟ࠊ㧗㏿໬ᡭἲ࡟㛵ࡍࡿ◊✲ࢆ⾜ࡗࡓࠋ୪ิ୍ḟඖ FFT ࢆ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝィ⟬⎔ቃ࡛ᐇ⾜ࡍࡿ㝿࡟ࠊ࡝ࡢࡼ࠺࡞࢔ࣝࢦࣜࢬ࣒ࡀᮃࡲࡋ࠸࠿࡟ࡘ࠸᳨࡚ウࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊࠕிࠖ࡟࠾ࡅࡿ୪ิ୍ḟඖ FFT ࡛ࡣࠊࡇࢀࡲ࡛࡟ᥦ᱌ࡉࢀ࡚࠸ࡓ୕ḟඖ⾲⌧ࡼࡾࡶࠊ஧ḟඖ⾲⌧ࢆ෌ᖐⓗ࡟㐺⏝ࡋ࡚ィ⟬ࡍࡿࡇ࡜࡛ࠊ࢟ࣕࢵࢩࣗࣄࢵࢺ⋡ࢆࡉࡽ࡟ྥୖࡉࡏࡿࡇ࡜ࡀ࡛ࡁࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
୪ิ୍ḟඖ FFT ࡟࠾࠸࡚ࡣࠊ඲య࡟㛵ࢃࡿᛶ⬟ࣃ࣓࣮ࣛࢱ࡜ࡋ࡚ࠊ඲ᑐ඲㏻ಙ᪉ᘧ
࡜ᇶᗏࠊࡑࡋ࡚ࣈࣟࢵࢡࢧ࢖ࢬࡀᏑᅾࡍࡿࡀࠊࡇࢀࡽ࡟ࡘ࠸࡚᭱㐺࡞ࣃ࣓࣮ࣛࢱࢆ⮬ືⓗ࡟ࢳ࣮ࣗࢽࣥࢢࡍࡿᶵᵓࢆࢯࣇࢺ࢙࢘࢔࡛ᐇ⌧ࡋࡓࠋࡑࡢ⤖ᯝࠊ୪ิ୍ḟඖ FFT ࡟
࠾࠸࡚ᐇ⾜᫬㛫ࡢከࡃࢆ༨ࡵ࡚࠸ࡿ඲ᑐ඲㏻ಙ࡟せࡍࡿ᫬㛫ࢆ኱ᖜ࡟๐ῶࡍࡿࡇ࡜࡟
ᡂຌࡋࡓࠋ

150

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩ࠕிࠖ࡟࠾ࡅࡿ୪ิ୍ḟඖ FFT ࡢᛶ⬟  HA-PACS ࡟࠾ࡅࡿ୪ิ୍ḟඖ FFT ࡢᛶ⬟ᅗ  㧗ᛶ⬟ FFT ࡢᛶ⬟ホ౯(2) Block Krylov 㒊ศ✵㛫཯᚟ἲ࡟㛵ࡍࡿ◊✲㸦ከ⏣㔝㸧 」ᩘᮏࡢྑ㎶࣋ࢡࢺࣝࢆࡶࡘ㐃❧୍ḟ᪉⛬ᘧࢆ㧗㏿࣭㧗⢭ᗘ࡟ゎࡃࡓࡵࡢ Block
Krylov 㒊ศ✵㛫཯᚟ἲࡢ◊✲ࢆ⾜ࡗࡓࠋBlock Krylov 㒊ศ✵㛫཯᚟ἲ࡛ࡣࠊྑ㎶࣋ࢡࢺࣝᩘࡀቑຍࡍࡿ࡜ᩘ್ⓗ࡟୙Ᏻᐃ࡞≧ἣ࡟㝗ࡾࠊṧᕪࡢⓎᩓࡸ೵⁫ࢆᘬࡁ㉳ࡇࡍࠋࡇࡢᩘ್ⓗ୙Ᏻᐃᛶࡣࠊ཯᚟㐣⛬࡛࣋ࢡࢺࣝࡢṇつ┤஺໬ࢆ⾜࠺ࡇ࡜࡛⦆࿴ࡉࢀࡿࡀࠊከ
ࡃࡢ₇⟬㔞ࢆせࡍࡿࠋ ᮏ◊✲࡛ࡣࠊṇつ┤஺໬ࡢᐇ⾜ࢆືⓗ࡟ุ᩿ࡍࡿ࢔ࣝࢦࣜࢬ࣒ࢆᵓ⠏ࡋࠊBlock
Krylov 㒊ศ✵㛫཯᚟ἲࡢ㧗㏿໬ࢆᅗࡗࡓࠋ᱁Ꮚ QCD ィ⟬࡛⌧ࢀࡿ㐃❧୍ḟ᪉⛬ᘧ㸦⾜ิࢧ࢖ࢬ㸸1, 572, 864, ྑ㎶࣋ࢡࢺࣝᩘ㸸12㸧࡟ᑐࡋ࡚ᐇ㦂ࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊBlock
BiCGGRRO ἲ࡟ᮏ࢔ࣝࢦࣜࢬ࣒ࢆ㐺⏝ࡍࡿࡇ࡜࡛ࠊᚑ᮶ἲ࡛࠶ࡿ Modified Block
BiCGSTAB ἲࡼࡾࡶ㧗㏿࠿ࡘᏳᐃ࡟㧗⢭ᗘ㏆ఝゎࢆ⏕ᡂ࡛ࡁࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ

1974.3 1939.1
1556.0 1476.7

1694.8151

No convergence

1900.7

No convergence

No convergence

No convergenceᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩      (a) Block BiCGGRRO ἲ ࠋ         (b) Modified Block
BiCGSTAB ἲࠋᅗ 5 ṇつ┤஺໬ࡢᐇ⾜ᅇᩘ๐ῶ࡟ࡼࡿ Block Krylov 㒊ศ✵㛫཯᚟ゎἲࡢィ⟬᫬㛫ኚ໬㸸⾜ิ࣋ࢡࢺࣝ✚ࠊ 㸸ṇつ┤஺໬ࠊ 㸸ࡑࡢ௚ࠋ㻌࢚࠙ࢿࣝࢠ࣮฼⏝᭱㐺໬࡟㛵ࡍࡿ◊✲ࠚ(బ⸨ࠊඣ⋢) NEDO ࢢ࣮ࣜࣥ IT ࣉࣟࢪ࢙ࢡࢺࠕ࢚ࢿࣝࢠ࣮฼⏝᭱㐺໬ࢹ࣮ࢱࢭࣥࢱᇶ┙ᢏ⾡ࡢ◊✲㛤Ⓨ㸭ࢹ࣮ࢱࢭࣥࢱࡢࣔࢹࣝタィ࡜⥲ྜホ౯ࠖ㸦ᖹᡂ 20 ᖺᗘ࠿ࡽᖹᡂ 24 ᖺᗘ㸧࡟࠾࠸࡚ࠊࢧ࣮ࣂࢩࢫࢸ࣒ࡢホ౯ᣦᶆ࡟㛵ࡍࡿ◊✲ࢆ⾜ࡗ࡚࠸ࡿࠋᮏᖺᗘࡣࠊGreenSLA⟇ᐃࡢࡓࡵࡢᐃ㔞ⓗホ౯࡟ࡘ࠸࡚ SEPCWeb ࢆ⏝࠸࡚⢭⦓໬ࡍࡿ࡜࡜ࡶ࡟ࠊ᭱⤊ᖺᗘ࡜ࡋ࡚ࡢࡲ࡜ࡵࢆ⾜ࡗࡓࠋSPECWeb ࡢホ౯࡛ࡣࠊQoS ࡢホ౯ࡀ࣋ࣥࢳ࣐࣮ࢡෆ࡟⤌ࡳ㎸ ࡲ ࢀ ࡚ ࠸ ࡿ ࡜ ࡜ ࡶ ࡟ ࠊ ࢧ ࣮ ࣂ ㈇ Ⲵ ࢆ ኚ ໬ ࡉ ࡏ ࡚ ࡑ ࡢ 㟁 ຊ ࠶ ࡓ ࡾ ࡢ ᛶ ⬟ PPW:
Performance per Watt ࢆホ౯ࡍࡿࡇ࡜ࡀྍ⬟࡜࡞ࡗ࡚࠸ࡿࠋࡑࡢ⤖ᯝࠊࢧ࣮ࣂ㈇Ⲵࡀ
㸣࡛࡞࠸ሙྜ࡟ࡣࠊࡑࡢ㈇Ⲵ࡟ᛂࡌࡓᛶ⬟࡟ⴠ࡜ࡋࡘࡘ┬࢚ࢿࣝࢠ࣮㐠⏝ࢆ⾜࠺ࡇ࡜࡟ࡼࡾ PPW ࢆྥୖࡉࡏࡿࡇ࡜ࡀྍ⬟࡛࠶ࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋࡇࢀࡽࡢ⤖ᯝࢆࡶ
࡜࡟ Green SLA ࡢ᭷ຠᛶࡢホ౯ࢆ⾜ࡗࡓࠋࢧ࣮ࣂࡢ㐠⏝ഃࡣ Green SLA ࡢ⠊ᅖ࡛┬࢚ࢿ㐠⏝ࢆ⾜࠺ࡇ࡜࡟ࡼࡾࠊ㟁ຊ࢟ࣕࢵࣉ࡞࡝࡟ᰂ㌾࡟ᑐᛂࡍࡿࡇ࡜ࡀྍ⬟࡟࡞ࡿࠋ୍
᪉ࠊ࣮ࣘࢨഃࡣ୍ᐃࡢᛶ⬟పୗࢆチᐜࡍࡿ௦ࢃࡾ࡟ࠊᩱ㔠ࡸ୍᫬ⓗ࡞ࣜࢯ࣮ࢫࡢ㏣ຍ࡞࡝ࡢ≉඾ࢆ┬࢚ࢿ㐠⏝ࡢ࢖ࣥࢭࣥࢸ࢕ࣈ࡜ࡋ࡚ᚓࡿࡇ࡜ࡀ࡛ࡁࡿ࡜⪃࠼ࡽࢀࡿࠋ
㻌
࠙LES Ẽ㇟ࢥ࣮ࢻࡢ୪ิ GPU ໬࡟㛵ࡍࡿ◊✲ࠚ㸦ᮔࠊሮ㸧 ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ᆅ⌫⎔ቃ◊✲㒊㛛ࡢ᪥ୗ෸ᩍᤵࡽࡢࢳ࣮࣒࡜ࡢඹྠ◊✲࡟ࡼࡾ㒔ᕷつᶍࡢẼ㇟࡟㛵ࡍࡿ Large Eddy Simulation (LES)ࢥ࣮ࢻࡢ୪ิ GPU ໬ࢆ㐍ࡵࡓࠋྠ◊✲㒊㛛࡛ࡣᆅᇦࣞ࣋ࣝࡢẼ㇟ࢩ࣑࣮ࣗࣞࢩࣙࣥ࡜ࡋ࡚ࠊ㒔ᕷࣔࢹࣝࢆᑐ㇟࡜ࡋ
ࡓ LES ィ⟬ࡢ◊✲ࢆ㐍ࡵ࡚࠾ࡾࠊ᫖ᖺᗘࡼࡾࡇࢀࡽࡢ㛤Ⓨࢥ࣮ࢻࡢ GPU ໬ࢆ㐍ࡵ࡚࠸ࡿࠋ
152

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩ ᫖ᖺᗘࡢ◊✲࡛ࡣࠊLES ࢥ࣮ࢻࢆ CUDA ໬ࡋࡓࡀࠊ௒ᖺᗘࡢ◊✲࡛ࡣ᪥ୗࢢ࣮ࣝࣉ
ࡢࢥ࣮ࢻኚ᭦࡟ᰂ㌾࡟ᑐᛂࡍࡿࡓࡵ࡟ࠊFortran ࢥ࣮ࢻࢆ࣮࣋ࢫ࡜ࡋࠊPGI CUDA
Fortran ࢥࣥࣃ࢖࡛ࣛ GPU ᑐᛂࡍࡿ࡜࠸࠺᪉㔪࡛ࢥ࣮ࢻ⛣᳜ࢆ⾜ࡗࡓࠋࢥ࣮ࢻ඲య୰ࠊ
༢⣧࡞ࢻ࣓࢖ࣥศ๭࡜࡞ࡗ࡚࠸࡞࠸ BiCGSTAB ἲ࡟ࡼࡿ⾜ิィ⟬௨እࡢ㒊ศࢆ᏶඲࡟
GPU ໬ࡋࠊᇶᮏⓗ࡟඲࡚ࡢࢹ࣮ࢱࢆ GPU ෆ࣓ࣔࣜ࡟㛢ࡌ㎸ࡵࠊ࣮࢝ࢿࣝ㛵ᩘ࿧ࡧฟࡋ࡜ I/O ࡢ࣮࢜ࣂ࣊ࢵࢻࢆ᭱ᑠ໬ࡋࡓࠋࡑࡢ⤖ᯝࠊHA-PACS ࣮࣋ࢫࢡࣛࢫࢱࡢࣀ࣮ࢻ
ᙜࡓࡾ 4GPU ࡢ࣓ࣔࣜࢆ᭱኱㝈฼⏝ࡋࡓࢣ࣮ࢫ࡛ࠊCPU ࡢࡳ㸦ࣀ࣮ࢻᙜࡓࡾ 16 core㸧ࢆ౑ࡗࡓሙྜ࡟ẚ࡭ࠊGPU㸦ࣀ࣮ࢻᙜࡓࡾ 4 ྎ㸧ࢆ౑ࡗࡓሙྜ࡛ࡣࠊ㛵ᩘ࡟ᛂࡌ࡚ 4.3
ࠥ4.7 ಸࡢ㧗㏿໬ࡀᚓࡽࢀࡓࠋࡋ࠿ࡋࠊBiCGSTAB ἲィ⟬ࡣ඲యィ⟬ࡢ⣙ 30%ࢆ༨ࡵࡿࡓࡵࠊࢥ࣮ࢻ඲య࡛ࡢຍ㏿ࡣ 1.3 ಸ⛬ᗘ࡟␃ࡲࡗࡓࠋ௒ᚋࠊࡇࡢ㒊ศࡶ᏶඲ GPU ໬ࡋࠊࡉࡽ࡟᭱㐺໬ࢆ᪋ࡋ࡚ᛶ⬟ࢆᨵၿࡋ࡚࠸ࡃணᐃ࡛࠶ࡿࠋ
࠙᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢ୪ิ GPU ໬࡟㛵ࡍࡿ◊✲ࠚ㸦ᮔ㸧
 G8 ከᅜ㛫ඹྠ◊✲ࡢ୍⎔࡜ࡋ࡚ࠊ᪥ᮏཎᏊຊ◊✲㛤Ⓨᶵᵓཬࡧ⡿ᅜࣉࣜࣥࢫࢺࣥ኱
Ꮫ࡜ࡢඹྠ◊✲࡟ࡼࡾࠊḟୡ௦᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢ୪ิ GPU ໬ࢆ⾜ࡗࡓࠋ๓⪅࡟࠾࠸࡚ࡣࠕிࠖ➼࡛㛤Ⓨ୰ࡢ GT5D ࢥ࣮ࢻࢆࠊᚋ⪅࡟࠾࠸࡚ࡣ BG/Q ➼࡛㛤Ⓨ୰ࡢ GTC-P ࢥ࣮ࢻࢆᑐ㇟࡜ࡍࡿࠋ
 GT5D ࢥ࣮ࢻ࡟ࡘ࠸࡚ࡣࠊPGI CUDA Fortran ࢆ⏝࠸࡚ HA-PACS ࣮࣋ࢫࢡࣛࢫࢱ࡬ࡢ
⛣᳜ࢆ⾜࠸ࠊ඲యࡢ⣙ 9 ๭ࡢࢥ࣮ࢻࢆ GPU ໬ࡋࠊࢹ࣮ࢱ࡟㛵ࡋ࡚ࡣ඲࡚ࢆ GPU ࣓ࣔࣜ࡟ಖᣢࡍࡿࡼ࠺࡟ࢥ࣮ࢻࢆసᡂࡋࡓࠋྛ㛵ᩘ࡟ࡘ࠸࡚ࡢᛶ⬟ࢳ࣮ࣗࢽࣥࢢࡀ୙༑ศ࡞ࡇ
࡜࡜ࠊ୍㒊㛵ᩘ࡟ࡘ࠸࡚ࡣ GPU ໬ࡀ᏶஢ࡋ࡚࠸࡞࠸ࡓࡵࠊ⌧᫬Ⅼ࡛ࡣ HA-PACS ࡢྠᩘࣀ࣮ࢻࡢ CPU ࡢࡳࢆ฼⏝ࡋࡓሙྜ࡟ẚ࡭ 2 ಸ⛬ᗘࡢ㏿ᗘྥୖ࡟␃ࡲࡗ࡚࠾ࡾࠊ௒ᚋ
ᨵၿࡋ࡚⾜ࡁࡓ࠸ࠋ
 GTC-P ࢥ࣮ࢻ࡟ࡘ࠸࡚ࡣ G8 ࣉࣟࢪ࢙ࢡࢺෆ࡛୪ิグ㏙ゝㄒ XcalableMP (XMP)ࡢᛂ
⏝౛࡜ࡋ࡚ࢥ࣮ࢹ࢕ࣥࢢࢆ㐍ࡵ࡚࠾ࡾࠊ㏲ḟ∧ࢥ࣮ࢻࢆ XMP ୍࡛᪦グ㏙ࡋࠊࡑࡢᚋ࡛
XMP-dev ᣑᙇࢆ⾜ࡗ࡚ GPU ໬ࡍࡿணᐃ࡛࠶ࡿࠋ௒ᖺᗘ࡟ࡘ࠸࡚ࡣ XMP ໬ࡢᇶᮏ᪉㔪࡜ணഛホ౯ࢆ⾜ࡗࡓࠋG8 ࣉࣟࢪ࢙ࢡࢺ᭱⤊ᖺᗘ࡛࠶ࡿḟᖺᗘ࡛ XMP/XMP-dev ໬ࢆ᏶஢ࡍࡿணᐃ࡛࠶ࡿࠋ
㻌࠙䝕䜱䝨䞁䝎䝤䝹䝅䝇䝔䝮䛾䛯䜑䛾䝔䝇䝖䝒䞊䝹ࠚ㸦బ⸨㸪ሮ㸧(1) ࢡࣛ࢘ࢻࢆ⏝࠸ࡓࢹ࢕࣌ࣥࢲࣈࣝ࡞୪ิศᩓࢩࢫࢸ࣒ࡢࡓࡵࡢࢸࢫࢺᨭ᥼⎔ቃ
D-Cloudࡇࢀࡲ࡛㸪JST-CRESTࠕᐇ⏝໬ࢆ┠ᣦࡋࡓ⤌㎸ࡳࢩࢫࢸ࣒⏝ࢹ࢕࣌ࣥࢲࣈ࣭ࣝ࢜࣌
࣮ࣞࢸ࢕ࣥࢢࢩࢫࢸ࣒ࠖ◊✲㡿ᇦ࡟࠾࠸࡚㸪ᡃࠎࡣ୪ิศᩓࢸࢫࢺ⎔ቃ D-Cloud ࢆ㛤Ⓨࡋ࡚ࡁࡓ㸬㧗࠸ಙ㢗ᛶ☜ಖࡢࡓࡵ࡟ࡣ␗࡞ࡿධຊ࡟ࡼࡿ⥙⨶ⓗ࡞ࢸࢫࢺᐇ⾜ࡸࣁ࣮ࢻ153

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩࢙࢘࢔ᨾ㞀࡟ᑐࡍࡿ⪏ᨾ㞀ᛶࡢࢸࢫࢺ࡞࡝ᵝࠎ࡞ࢸࢫࢺࡀᚲせ࡛㸪ࡑࢀࡽࢆᐇ⾜ࡍࡿ࡟ࡣ㠀ᖖ࡟᫬㛫࡜ᡭ㛫ࡀ࠿࠿ࡿ㸬D-Cloud ࡛ࡣࣇ࢛ࣝࢺ࢖ࣥࢪ࢙ࢡࢩࣙࣥྍ⬟࡞௬᝿࣐ࢩ
ࣥࢆ⏝࠸࡚௬᝿ࢹࣂ࢖ࢫ࡛ࣞ࣋ࣝࡢᨾ㞀࡟ࡘ࠸࡚ࡢࢸࢫࢺࡀྍ⬟࡛࠶ࡿࡔࡅ࡛࡞ࡃ㸪≀⌮࣐ࢩࣥ⩌㸪࠾ࡼࡧ௬᝿࣐ࢩࣥࢆࢡࣛ࢘ࢻ࡜ࡋ࡚⟶⌮ࡍࡿࡇ࡜࡟ࡼࡾࠊከࡃࡢィ⟬㈨※
ࢆᰂ㌾࡟฼⏝ࡍࡿࡇ࡜ࡀ࡛ࡁ㸪ከࡃࡢࢣ࣮ࢫ࡟ࡘ࠸࡚ࡢࢸࢫࢺసᴗࢆ⮬ື໬ࡍࡿࡇ࡜ࡀ
࡛ࡁࡿ⎔ቃࢆᥦ౪ࡍࡿ㸬ྠ᫬࡟㸪ᮾ኱▼ᕝࢳ࣮࣒࡜ඹྠ࡛㸪ྛ✀ࡢᐃ㔞ⓗ࡞ࢹ࢕࣌ࣥࢲ
ࣅࣜࢸ࢕ᣦᶆࡢࢩࢫࢸ࣐ࢸ࢕ࢵࢡ࡞ィィࢆᨭ᥼ࡍࡿࡇ࡜ࢆ┠ⓗ࡟ࠊࢹ࢕࣌ࣥࢲࣅࣜࢸ࢕

ࢶ࣮ࣝ⩌ DS-Bench Toolset ࢆ㛤Ⓨࡋ࡚ࡁࡓ㸬ࣁ࣮ࢻ࢙࢘࢔␗ᖖࠊࢯࣇࢺ࢙࢘࢔ࣂ

ࢢࠊ㐣㈇Ⲵࠊேⓗ࣑ࢫ࡜࠸ࡗࡓᵝࠎ࡞␗ᖖࢆ⣔⤫❧࡚࡚ᢅ࠺ࡇ࡜࡟ࡼࡗ࡚ࠊ኱つᶍ࡞ࢩࢫࢸ࣒ࢸࢫࢺࢆᐇ⌧ࡋࠊከࡃࡢࢸࢫࢺࣃࢱ࣮ࣥࢆ⏝࠸ࡓ」㞧࡞ࢸࢫࢺࢆຍ㏿ࡍࡿࡇ࡜ࡀ
࡛ࡁࡿ㸬ࡉࡽ࡟ࠊࢩࢫࢸ࣒ࡢࢹ࢕࣌ࣥࢲࣅࣜࢸ࢕࡟ࡘ࠸࡚ࢫࢸ࣮ࢡ࣍ࣝࢲ࡜ࡢ㛫࡛㆟ㄽࡍࡿࡓࡵࡢ D-Case Editor ࡜㐃ᦠࡍࡿࡇ࡜ࡀ࡛ࡁࡿ
௒ᖺᗘࡣ㸪ᡃࠎࡢ㛤Ⓨࡋࡓ D-Cloud ࡟㛵ࡍࡿ◊✲ᡂᯝ㸪࠾ࡼࡧ DS-Bench ࡢࢩࢫࢸ࣒ࢸࢫࢺ⎔ቃ࡜ࡋ࡚⤫ྜࢆ⾜ࡗࡓ DS-Bench Toolset ࡢ◊✲ᡂᯝ࡟ࡘ࠸࡚Ⓨ⾲ࢆ⾜ࡗࡓ㸬
㻌㻌
㻌
4.

1.

እ㒊㈨㔠ࡢ⋓ᚓ≧ἣᩥ㒊⛉Ꮫ┬࣭ᑗ᮶ࡢ HPCI ࢩࢫࢸ࣒ࡢ࠶ࡾ᪉ࡢㄪᰝ◊✲ࠕ₇⟬ຍ㏿ᶵᵓࢆᣢࡘᑗ
᮶ࡢ HPCI ࢩࢫࢸ࣒࡟㛵ࡍࡿㄪᰝ◊✲ࠖH24 ᖺᗘ 32,148 ༓෇㸦௦⾲㸸బ⸨୕ஂ㸧2.

ᩥ㒊⛉Ꮫ┬㸪⛉Ꮫᢏ⾡ヨ㦂◊✲ጤク஦ᴗ㸪
ࠕHPCI ඹ㏻㐠⏝ࢩࢫࢸ࣒ࡢᩚഛ㸦ඹ⏝ࢫࢺ࣮ࣞࢪࢯࣇࢺ࢙࢘࢔ᩚഛ㸧ࠖ㸪 H24 ᖺᗘ㸪73,700 ༓෇㸦ᴗົ୺௵⪅బ⸨୕ஂ㸪
ᢸᙜ㈐௵⪅ᘓ㒊ಟぢ㸧

3.

JST CREST ◊✲㡿ᇦࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝ㧗ᛶ⬟ィ⟬࡟㈨ࡍࡿࢩࢫࢸ࣒ࢯࣇࢺ࢘
࢙࢔ᢏ⾡ࡢ๰ฟࠖ㸪ࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝࢹ࣮ࢱ࢖ࣥࢸࣥࢩࣈࢧ࢖࢚ࣥࢫࡢࡓࡵࡢ
ࢩࢫࢸ࣒ࢯࣇࢺ࢙࢘࢔ࠖ㸪H23 ᖺᗘࠥH27 ᖺᗘ㸪241,941 ༓෇㸦௦⾲㸸ᘓ㒊ಟぢ㸧

4.

JST CREST ◊✲㡿ᇦࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝ㧗ᛶ⬟ィ⟬࡟㈨ࡍࡿࢩࢫࢸ࣒ࢯࣇࢺ࢘
࢙࢔ᢏ⾡ࡢ๰ฟࠖ㸪ࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝ᫬௦࡟ྥࡅࡓ₇⟬ຍ㏿ᶵᵓ࣭㏻ಙᶵᵓ⤫ྜ⎔ቃࡢ◊✲㛤Ⓨࠖ
㸪H24ࠥH29 ᖺᗘ㸪312,380 ༓෇㸦௦⾲㸸ᮔὈ♸㸧

5.

JST CREST ◊✲㡿ᇦࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝ㧗ᛶ⬟ィ⟬࡟㈨ࡍࡿࢩࢫࢸ࣒ࢯࣇࢺ࢘
࢙࢔ᢏ⾡ࡢ๰ฟࠖ㸪ࠕᩘ್ィ⟬ࣛ࢖ࣈࣛࣜ࡟ࡼࡿ㉸୪ิ」ྜࢩࢫࢸ࣒ࡢ㝵ᒙⓗᢳ㇟໬࡟㛵ࡍࡿ◊✲ H24ࠥ26 ᖺᗘ 15,132 ༓෇㸦H24㸧㸦ඹྠ◊✲⪅㸸㧗ᶫ኱௓㸧

6.

᪥௖ᡓ␎ࣉࣟࢢ࣒ࣛࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢࡢࡓࡵࡢࣉࣟࢢࣛ
࣑ࣥࢢゝㄒᣑᙇ࠾ࡼࡧᩘ್ィ⟬࢔ࣝࢦࣜࢬ࣒ࠊᛶ⬟ホ౯ࠊ኱つᶍࢹ࣮ࢱ⟶⌮ᢏ⾡ࠖࠊ
H22ࠥH24 ᖺᗘ 11,000 ༓෇㸦௦⾲㸸బ⸨୕ஂ㸧

7.

NEDOࠕࢢ࣮ࣜࣥࢿࢵࢺ࣮࣡ࢡ࣭ࢩࢫࢸ࣒ᢏ⾡◊✲㛤Ⓨࣉࣟࢪ࢙ࢡࢺ(ࢢ࣮ࣜࣥ IT
ࣉࣟࢪ࢙ࢡࢺ)/࢚ࢿࣝࢠ࣮฼⏝᭱㐺໬ࢹ࣮ࢱࢭࣥࢱᇶ┙ᢏ⾡ࡢ◊✲㛤Ⓨ/ࢹ࣮ࢱࢭ
154

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩ࣥࢱࡢࣔࢹࣝタィࠖH20ࠥH24 ᖺᗘ 3,780 ༓෇㸦௦⾲㸸బ⸨୕ஂ㸧᪥ᮏᏛ⾡᣺⯆఍࣭ከᅜ㛫ᅜ㝿◊✲༠ຊ஦ᴗࠕECS㸸࢚ࢡࢧࢫࢣ࣮࣭ࣝࢥࣥࣆ࣮ࣗ

8.

ࢸ࢕ࣥࢢ࡟ࡼࡿ⢭⦓࡞Ẽೃࢩ࣑࣮ࣗࣞࢩࣙࣥࡢᐇ⌧ࠖH23ࠥH25 ᖺᗘ 11,200 ༓෇㸦௦⾲㸸బ⸨୕ஂ㸧᪥ᮏᏛ⾡᣺⯆఍࣭ከᅜ㛫ᅜ㝿◊✲༠ຊ஦ᴗࠕNuFuSE㸸࢚ࢡࢧࢫࢣ࣮࣭ࣝࢥࣥࣆ

9.

࣮ࣗࢸ࢕ࣥࢢ࡟࠾ࡅࡿ᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࠖH23ࠥH25 ᖺᗘ 25,920 ༓෇㸦௦⾲㸸ᮔὈ♸㸧
10. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ⱝᡭ◊✲ (B)ࠕ」ᩘྑ㎶㡯ࢆࡶࡘ㐃❧୍ḟ᪉⛬ᘧࡢ㧗㏿࣭㧗⢭ᗘồゎἲࡢ㛤Ⓨ࡜⛉Ꮫᢏ⾡ィ⟬࡬ࡢᛂ⏝ࠖ780 ༓෇㸦௦⾲㸸ከ⏣㔝ᐶே㸧
11. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ᇶ┙◊✲ (B)ࠕ᭷㝈⠇Ⅼἲ࣭ቃ⏺⠇Ⅼἲࡢ᏶඲࣓ࢵࢩࣗࣞࢫ໬
࡜ࡑࡢᕤᏛⓗᛂ⏝ࠖ195 ༓෇㸦ศᢸ㸸ከ⏣㔝ᐶே㸧
12. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ⱝᡭ◊✲ (B)ࠕ」ᩘྑ㎶㡯ࢆࡶࡘ㐃❧୍ḟ᪉⛬ᘧࡢ㧗㏿࣭㧗⢭ᗘồゎἲࡢ㛤Ⓨ࡜⛉Ꮫᢏ⾡ィ⟬࡬ࡢᛂ⏝ࠖ780 ༓෇㸦௦⾲㸸㧗ᶫ኱௓㸧
13. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ᇶ┙◊✲ (B)ࠕ᭷㝈⠇Ⅼἲ࣭ቃ⏺⠇Ⅼἲࡢ᏶඲࣓ࢵࢩࣗࣞࢫ໬
࡜ࡑࡢᕤᏛⓗᛂ⏝ࠖ195 ༓෇㸦ศᢸ㸸㧗ᶫ኱௓㸧
14. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ᇶ┙◊✲ (C)ࠕ࢚ࢡࢧࢫࢣ࣮ࣝィ⟬⎔ቃ࡟ྥࡅࡓ㧗㏿ࣇ࣮࢚ࣜኚ᥮ࡢ࢔ࣝࢦࣜࢬ࣒࡟㛵ࡍࡿ◊✲ࠖH24ࠥ26 ᖺᗘ 1,560 ༓෇㸦H24㸧
㸦௦⾲㸸㧗
ᶫ኱௓㸧
15. ⛉Ꮫ◊✲㈝⿵ຓ㔠 ᪂Ꮫ⾡㡿ᇦ◊✲㸦◊✲㡿ᇦᥦ᱌ᆺ㸧ࠕ኱つᶍ୪ิ⎔ቃ࡟࠾ࡅࡿ
ᩘ್ィ⟬࢔ࣝࢦࣜࢬ࣒ࠖH22ࠥ26 ᖺᗘ 3,900 ༓෇㸦H24㸧㸦ศᢸ㸸㧗ᶫ኱௓㸧
㻌
5.

◊✲ᴗ⦼

䠄䠍䠅◊✲ㄽᩥ
1.

Adnan, M. Sato, “Dynamic Multiple Work Stealing Strategy for Flexible Load Balancing”,
IEICE Transactions 95-D(6): 1565-1576 (2012)

2.

A. Hori, J. Lee, M. Sato, “Audit: A new synchronization API for the GET/PUT protocol”,
J. Parallel Distrib. Comput. 72(11): 1464-1470 (2012)3.

᳚ᮌ኱ᆅ, 㧗ᶫ኱௓, “GPU࡟࠾ࡅࡿ3ಸ࣭4ಸ⢭ᗘᾋືᑠᩘⅬ₇⟬ࡢᐇ⌧࡜ᛶ⬟ホ౯,”᝟ሗฎ⌮Ꮫ఍ㄽᩥㄅ ࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢࢩࢫࢸ࣒, Vol. 6, No. 1, pp. 6677, 2013.

4.

M. Naito, H. Tadano, T. Sakurai, “A modified Block IDR(s) method for computing highaccuracy solutions”, JSIAM Letters, Vol. 4, pp. 25-28, 2012.

5.

ྜ⏣ ᠇ே, ᮾ⏣Ꮫ, ᆏ᰿ᰤస, ኳ㔝ᾈᩥ, ᑠᯘඞᚿ, Ჷᮅ㞞ᬕ, Ụᕝ㝯㍜, ᘓ㒊ಟぢ, 㬞ᚿ⏣Ⰻ࿴, ⁪⃝┿୍ᮁ, Ọ஭஽, ᒾୗṊྐ, ▼ᕝ⿱,“㧗ᛶ⬟ศᩓィ⟬⎔ቃࡢࡓࡵࡢㄆドᇶ┙ࡢタィ”, ㄽᩥㄅࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢࢩࢫࢸ࣒(ACS), ᝟ሗฎ⌮Ꮫ఍, No.5, Vol.5, pp.90-102, 2012155ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

6.

Y. Kodama, S. Itoh, T. Shimizu, S. Sekiguchi, H. Nakamura and N. Mori, “Imbalance ofCPU temperatures in a blade system and its impact for power consumption of fans”,
Journal of Cluster Computing, Springer, Vol.16, No.1, pp.27-37, 2013.

䠄䠎䠅Ꮫ఍Ⓨ⾲䠄A䠅ᣍᚅㅮ₇
1.

M. Sato, " The next step for Post-Petascale Computing in Japan", HPC in Asia Workshop,
ISC 2012, June 2012.

2.

T. Boku, “HA-PACS Project: Challenge for Next Step of Accelerating Computing”,
ATIP/A*CRC Workshop, Singapore, May 2012.

3.

T. Boku, “HA-PACS: Next Step for Scientific Frontier by Accelerated Computing”, GTC
Japan 2012, Tokyo, July 2012.

4.

T. Boku, “HPC Trend in Asia”, HPC in China Workshop (ISC2012), Hamburg, June 2012.

5.

D. Takahashi, “Automatic Tuning for Parallel FFTs”, 2013 Conference on Advanced
Topics and Auto Tuning in High Performance and Scientific Computing (2013@^2HPSC),
National Taiwan University, Taipei, Taiwan, March 28, 2013.

6.

D. Takahashi, “Automatic Tuning for Parallel FFTs on Clusters of Multi-Core Processors”,
Special Session: Auto-Tuning for Multicore and GPU (ATMG) (held in conjunction withIEEE MCSoC-12), The University of Aizu, Aizu, Japan, September 22, 2012.

7.

O. Tatebe, “File System for Post-Petascale Data-Intensive Computing”, International
Supercomputing Conference, 20128.

ᮔ Ὀ♸, “ࠕிࠖࢆࡣࡌࡵ࡜ࡍࡿ᭱ඛ➃ࢫ࣮ࣃ࣮ࢥࣥࣆ࣮ࣗࢱࡢືྥ”, ᰾⼥ྜ࢚ࢿࣝࢠ࣮㐃ྜㅮ₇఍2012, 2012ᖺ6᭶.

9.

ከ⏣㔝 ᐶே, “」ᩘྑ㎶࣋ࢡࢺࣝࢆࡶࡘ㐃❧୍ḟ᪉⛬ᘧࡢᩘ್ゎἲ࡜୪ิᅛ᭷್ィ⟬࡬ࡢᛂ⏝”, ➨5ᅇ᪥ᮏᩘᘧฎ⌮Ꮫ఍⌮ㄽศ⛉఍㸤ࢩࢫࢸ࣒ศ⛉఍ྜྠ◊✲఍,
2012.

10. ඣ⋢♸ᝋ, “FPGA ࡢᛂ⏝஦౛ 㹼୪ิィ⟬ᶵ࡜ࢿࢵࢺ࣮࣡ࢡ㹼, ” 㟁Ꮚ᝟ሗ㏻ಙᏛ
఍ࣜࢥࣥࣇ࢕ࢠࣕࣛࣈࣝࢩࢫࢸ࣒◊✲఍, 2012.
11. ሮᩄ༤͆)3*$࡟ࡼࡿ7LJKWO\&RXSOHG$FFHOHUDWRUVྥࡅ㏻ಙᶵᵓࡢᐇ⌧͇㸪ḟୡ௦5+:๰㐀◊✲఍ -$&251 㸬
䠄B䠅䛭䛾௚䛾Ꮫ఍Ⓨ⾲䠄ᰝㄞ௜䠅
1. M. Nakao, J. Lee, T. Boku, M. Sato, “Productivity and Performance of Global-View
Programming with XcalableMP PGAS Language”, CCGRID 2012: 402-409, 2012.
2. M. Tsuji, M. Sato, A. S. Tanabe, Y. Inagaki, T. Hashimoto, “An asynchronous parallel156

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

genetic algorithm for the maximum likelihood phylogenetic tree search”, IEEE Congress on
Evolutionary Computation 2012: 1-8, 2012.
3. T. Abe, M. Sato, “On-the-Fly Synchronization Checking for Interactive Programming in
XcalableMP”, Proc. of P2S2 (with ICPP 2012), 29-37, 2012.
4. H. Yoshizawa and D. Takahashi, “Automatic Tuning of Sparse Matrix-Vector Multiplication
for CRS format on GPUs”, Proc. 2012 IEEE 15th International Conference on
Computational Science and Engineering (CSE 2012), pp. 130136 (2012).
5. D. Takahashi, “An Implementation of Parallel 2-D FFT Using Intel AVX Instructions on
Multi-Core Processors”, Proc. 12th International Conference on Algorithms andArchitectures for Parallel Processing (ICA3PP 2012), Part II, Lecture Notes in Computer
Science, No. 7440, pp. 197205, Springer-Verlag (2012).
6. D. Takahashi, A. Uno and M. Yokokawa, “An Implementation of Parallel 1-D FFT on the K
computer”, Proc. 2012 IEEE 14th International Conference on High Performance
Computing and Communications (HPCC-2012), pp. 344350 (2012).
7. Y. Miki, D. Takahashi and M. Mori, “A Fast Implementation and Performance Analysis ofCollisionless N-body Code Based on GPGPU”, Proc. International Conference on
Computational Science (ICCS 2012), Procedia Computer Science, Vol. 9, pp. 96105,
Elsevier (2012).
8. T. Nomizu, D. Takahashi, J. Lee, T. Boku and M. Sato, “Implementation of XcalableMP
Device Acceleration Extention with OpenCL”, Proc. 2012 IEEE 26th International Paralleland Distributed Processing Symposium Workshops & PhD Forum (IPDPSW 2012),
Multicore and GPU Programming Models, Languages and Compilers Workshop (PLC2012), pp. 23942403 (2012).
9. D. Mukunoki and D. Takahashi, “Implementation and Evaluation of Triple Precision BLAS
Subroutines on GPUs”, Proc. 2012 IEEE 26th International Parallel and Distributed
Processing Symposium Workshops & PhD Forum (IPDPSW 2012), The 13th Workshop on
Parallel and Distributed Scientific and Engineering Computing (PDSEC-12), pp.
13781386 (2012).
10. D. Mukunoki and D. Takahashi, “Performance Comparison of Double, Triple andQuadruple Precision Real and Complex BLAS Subroutines on GPUs”, Proc. ATIP/A*CRC
Workshop on Accelerator Technologies for High-Performance Computing: Does Asia Leadthe Way? (ATIP/A*CRC Workshop '12), pp. 788790 (2012).
11. T. Odajima, T. Boku, T. Hanawa, J. Lee, M. Sato, "GPU/CPU Work-Sharing with Parallel
Language XcalableMP-dev for Parallelized Accelerated Computing", Proc. of P2S2-2012(with ICPP2012), Pittsburgh, CD-ROM, 2012.
157

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

12. L.Du, T. Sakurai, H. Tadano, M. Naito, “IDR(s) for linear systems with multiple shifts andmultiple right-hand sides”, The 8th East Asia SIAM Conference (EASIAM2012), 2012.
13. T. Sakurai, Y. Futamura, L. Du, H. Tadano, “A hierarchical parallel implementation of acontour integral-based eigensolver on Trilinos”, SIAM Conference on Computational
Science and Engineering, 2013.
14. Masahiro Tanaka, Osamu Tatebe, “Workflow Scheduling to Minimize Data Movement
using Multi-constraint Graph Partitioning”, Proceedings of IEEE/ACM International
Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp.65-72, doi:
10.1109/CCGrid.2012.134, 201215. Shun Ishiguro, Jun Murakami, Yoshihiro Oyama and Osamu Tatebe, “Optimizing Local File
Accesses for FUSE-Based Distributed Storage”,

Proceedings of the international

workshop on data-intensive scalable computing systems, 2012.
16. H. Fujita, Y. Matsuno, T. Hanawa, M. Sato, S. Kato, and Y. Ishikawa, "DS-Bench Toolset:
Tools for Dependability Benchmarking with Simulation and Assurance," 42nd IEEE/IFIP
International Conference on Dependable Systems and Networks (DSN 2012), 8 pages, Jun.
2012.
17. బ⸨ెᕞ, 㧗ᶫ኱௓, “኱つᶍ࡞ᑐᒁ࡟ᇶ࡙࠸ࡓᩍᖌࢹ࣮ࢱࡢ㔜せᗘࡢᏛ⩦”, ➨ 17ᅇࢤ࣮࣒ࣉࣟࢢ࣑ࣛࣥࢢ࣮࣡ࢡࢩࣙࢵࣉ, pp. 2229 (2012).
18. ྜ⏣᠇ே, ᮾ⏣Ꮫ, ᆏ᰿ᰤస, ኳ㔝ᾈᩥ, ᑠᯘඞᚿ, Ჷᮅ㞞ᬕ, Ụᕝ㝯㍜, ᘓ㒊ಟぢ,㬞ᚿ⏣Ⰻ࿴, ⁪⃝┿୍ᮁ, Ọ஭஽, ᒾୗṊྐ, ▼ᕝ⿱, “㧗ᛶ⬟ศᩓィ⟬⎔ቃࡢࡓࡵࡢ
ㄆドᇶ┙ࡢタィ”, ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS2012 ㄽᩥ㞟,
pp.227-236, 201219. ᡪ㇂ ㇦, ୕ᮌ ὒᖹ, ᮔ Ὀ♸, ᳃ ṇኵ, ୰㔛 ┤ே, “㔜ຊከయ⣔⏝ Tree Code ࡢ୪ิGPU ໬࡟ࡼࡿィ⟬ຍ㏿”, 2013 ᖺࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ࡜ィ⟬⛉Ꮫࢩ࣏ࣥࢪ࣒࢘ HPCS2013 ㄽᩥ㞟, 2013.
20. 㮚ὠ෤ᑗ, ᘓ㒊ಟぢ, “ࣟࢢᵓ㐀໬ࣇ࢓࢖ࣝࢩࢫࢸ࣒ mylfs ࡢタィ࡜ึᮇホ౯”, ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS2012 ࣏ࢫࢱ࣮Ⓨ⾲, 2012.
21. ᑠ⏣ᔱ ဴဢ㸪ᮤ ⌋Ἢ㸪ᮔ Ὀ♸㸪బ⸨ ୕ஂ, “XMP-dev ࡟ᇶ࡙ࡃ CPU/GPU ࣁ࢖ࣈ
ࣜࢵࢻ㈇Ⲵศᩓࢩࢫࢸ࣒”, ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS2012 ࣏ࢫࢱ࣮Ⓨ⾲, 2012.
22. 㮚ὠ෤ᑗ , ᖹ㈡ᘯᖹ , ᘓ㒊ಟぢ , Gabriel Antoniu, “ᗈᇦศᩓࣇ࢓࢖ࣝࢩࢫࢸ ࣒
Blobseer-wan/HGMDS ࡢタィ࡜ึᮇホ౯”, 2013 ᖺࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ
࢕ࣥࢢ࡜ィ⟬⛉Ꮫࢩ࣏ࣥࢪ࣒࢘ HPCS2013 ࣏ࢫࢱ࣮Ⓨ⾲, 2013.
23. ⸨⏣ ඾ஂ㸪ያ㈡ ⚽⏨㸪ᮔ Ὀ♸㸪஭ᡞᮧ Ὀᏹ, “GPU ࢡࣛࢫࢱ࡟࠾ࡅࡿ᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢᐇ⿦”, 2013 ᖺࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ࡜ィ158

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩⟬⛉Ꮫࢩ࣏ࣥࢪ࣒࢘ HPCS2013 ࣏ࢫࢱ࣮Ⓨ⾲, 2013.
䠄C䠅䛭䛾௚䛾Ꮫ఍Ⓨ⾲䠄ᰝㄞ↓䠅1.

᳚ᮌ኱ᆅ, 㧗ᶫ኱௓㸸GPU ࡟࠾ࡅࡿ㧗㏿࡞ CRS ᙧᘧ␯⾜ิ࣋ࢡࢺࣝ✚ࡢᐇ⿦, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2013-HPC-138, No. 5 (2013).

2.

᳚ᮌ኱ᆅ, 㧗ᶫ኱௓㸸GPU ࡟࠾ࡅࡿ 4 ಸ⢭ᗘ₇⟬ࢆ⏝࠸ࡓ␯⾜ิ཯᚟ゎἲࡢᐇ⿦࡜ホ౯, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-ARC-202, 2012-HPC-137, No. 37 (2012).

3.

୕ᮌὒᖹ, 㧗ᶫ኱௓, ᳃ṇኵ㸸኱つᶍ GPU ࢡࣛࢫࢱ࡟࠾ࡅࡿ N యィ⟬ࢥ࣮ࢻࡢ₇⟬ᛶ⬟࡜ࢫࢣ࣮ࣛࣅࣜࢸ࢕ࡢホ౯, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-136, No. 1(2012).

4.

㧗ᶫ኱௓㸸࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝィ⟬⎔ቃ࡟ྥࡅࡓ୪ิ FFT ࡢ⮬ືࢳ࣮ࣗࢽࣥࢢ, ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ 2012 ᖺᗘᖺ఍ㅮ₇ண✏㞟, pp. 285286 (2012).

5.

ྜྷ⃝኱ᶞ, 㧗ᶫ኱௓㸸GPU ࡟࠾ࡅࡿ CRS ᙧᘧ␯⾜ิ࣋ࢡࢺࣝ✚ࡢ⮬ືࢳ࣮ࣗࢽࣥ
ࢢ, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-135, No. 31 (2012).

6.

㧗ᶫ኱௓㸸୪ิ FFT ࡟࠾ࡅࡿ⮬ືࢳ࣮ࣗࢽࣥࢢ, ィ⟬ᕤᏛㅮ₇఍ㄽᩥ㞟, Vol. 17,
E-7-2 (2012).

7.

ෆ⸨ ⌮኱, ከ⏣㔝 ᐶே, Ḉ஭ 㕲ஓ, Block IDR(s)ἲ࡟࠾ࡅࡿṧᕪ೵⁫ࡢᅇ㑊ἲ࡟ࡘ࠸࡚, ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ 2012 ᖺᗘᖺ఍, pp. 89-90, 2012.

8.

ከ⏣㔝 ᐶே, Ḉ஭ 㕲ஓ, ഇ཰᮰ࢆᅇ㑊ࡍࡿ Block Krylov 㒊ศ✵㛫཯᚟ἲࡢᏳᐃ໬
࡜ィ⟬㔞๐ῶ࡟ࡘ࠸࡚, ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ 2012 ᖺᗘᖺ఍, pp. 287-288, 2012.

9.

௒಴ ᬡ, ᮭ ☨, ከ⏣㔝 ᐶே, 」ᩘྑ㎶࣋ࢡࢺࣝࢆᣢࡘ⥺ᙧ᪉⛬ᘧ࡟ᑐࡍࡿ
Weighted Block GMRES ἲ, ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ࠕ⾜ิ࣭ᅛ᭷್ၥ㢟ࡢゎἲ࡜ࡑࡢᛂ
⏝ࠖ◊✲㒊఍ ➨ 14 ᅇ◊✲఍, 2012.

10. ⏣୰ᫀᏹ, ᘓ㒊ಟぢ, ኱つᶍ࣮࣡ࢡࣇ࣮ࣟ࡟ᑐᛂࡋࡓ Pwrake ࢩࢫࢸ࣒ࡢタィ࡜ᐇ⿦, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-135(14), pp.1-7, 201211. ኱す೺ኴ, ᘓ㒊ಟぢ, ෕㛗➢ྕࢆ⏝࠸ࡓࢧ࣮ࣂ࣐ࢩࣥ㛫࡛ࡢࢹ࣮ࢱศᩓᡭἲࡢ᳨ウ, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-135(22), pp.1-7, 201212. 㮚ὠ෤ᑗ, ᘓ㒊ಟぢ, 㧗㏿࡞ࢫࢺ࣮ࣞࢪ࡟㐺ࡋࡓࣟࢢᵓ㐀໬ࣇ࢓࢖ࣝࢩࢫࢸ࣒
MyLFS ࡢタィ࡜ホ౯, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-135(27), pp.1-7, 201213. ᖹ㈡ᘯᖹ, ᘓ㒊ಟぢ, ࣀࣥࣈࣟࢵ࢟ࣥࢢࢺࣛࣥࢨࢡࢩࣙࣥ࡟ᇶ࡙ࡃศᩓࣇ࢓࢖ࣝ
ࢩࢫࢸ࣒ࡢࡓࡵࡢศᩓ࣓ࢱࢹ࣮ࢱࢧ࣮ࣂࡢタィ࡜ᐇ⿦, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌,
2012-HPC-135(28), pp.1-9, 201214. ኱㎷ᘯ㈗, ᘓ㒊ಟぢ, Infiniband ࢆ⏝࠸ࡓࣇ࢓࢖ࣝ࢔ࢡࢭࢫࡢ㧗㏿໬, ᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-135(29), pp.1-6, 201215. ኱㎷ᘯ㈗, ᘓ㒊ಟぢ, RDMA ࡟ࡼࡿప࣮࢜ࣂ࣊ࢵࢻࣇ࢓࢖ࣝ࢔ࢡࢭࢫ࡜෕㛗グ㘓,159

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2012-HPC-137(29), pp.1-6, 201216. 㮚ὠ෤ᑗ , ᖹ㈡ᘯᖹ , ᘓ㒊ಟぢ , Gabriel Antoniu, ᗈᇦศᩓࣇ࢓࢖ࣝࢩࢫࢸ࣒BlobSeer-wan/HGMDS ࡢタィ࡜ホ౯.᝟ሗฎ⌮Ꮫ఍◊✲ሗ࿌, 2013-HPC-138(22),pp.1-7, 201317. ᱵ⏣ ᏹ᫂, ሮ ᩄ༤, ᗉྖ ග⏨, ᮔ Ὀ♸, "ศᏊ㌶㐨ィ⟬ࡢ GPGPU ໬࡟ྥࡅࡓ⾜ิຍ⟬ᡭἲࡢᥦ᱌", 2013-HPC-138, 2013.
18. ⸨⏣ ඾ஂ, ያ㈡ ⚽⏨, ᮔ Ὀ♸, ஭ᡞᮧ Ὀᏹ, "GPU ࢡࣛࢫࢱ࡟࠾ࡅࡿ᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢᐇ⿦", 2013-HPC-138, 2013.
19. ᑠ⏣ᔱ ဴဢ, ᮤ ⌋Ἢ, ᮔ Ὀ♸, బ⸨ ୕ஂ, ሮ ᩄ༤, ඣ⋢ ♸ᝋ, RaymondNamyst, Samuel Thibault, Olivier Aumage, "GPU ࢡࣛࢫࢱྥࡅ୪ิゝㄒ XMP-dev ࡟࠾ࡅࡿ GPU/CPU ༠ㄪィ⟬", 2013-HPC-138, 2013.
20. ሮᩄ༤, ඣ⋢♸ᝋ, ᮔὈ♸, బ⸨୕ஂ, "Tightly Coupled Accelerators ࢔࣮࢟ࢸࢡࢳࣕ
ྥࡅ㏻ಙᶵᵓࡢணഛホ౯", 2012-ARC-202(13), pp.1-8, 2012.
21. ⸨⏣඾ஂ, ያ㈡⚽⏨, ᮔὈ♸, ஭ᡞᮧὈᏹ, "᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢ GPUࢡࣛࢫࢱྥࡅ᭱㐺໬", 2012-HPC-135, 2012.
22. ᑠ⏣ᔱဴဢ, ᮤ⌋Ἢ, ᮔὈ♸, బ⸨୕ஂ, ሮᩄ༤, ඣ⋢♸ᝋ, Raymond Namyst,
Samuel Thibault, Olivier Aumage, "GPU ࢡࣛࢫࢱ࡟࠾ࡅࡿ GPU/CPU ࣁ࢖ࣈࣜࢵࢻ࣭
ࣉࣟࢢ࣑ࣛࣥࢢ⎔ቃ", 2012-HPC-135, 2012.
23. ᡪ㇂㇦, ୕ᮌὒᖹ, ᮔὈ♸, ᳃ṇኵ, ୰㔛┤ே, "㔜ຊከయ⣔⏝ Tree Code ࡢ୪ิ GPU
໬", 2012-HPC-135, 2012.
24. ሮᩄ༤, ඣ⋢♸ᝋ, ᮔὈ♸, బ⸨୕ஂ, "Tightly Coupled Accelerators ࢔࣮࢟ࢸࢡࢳࣕ
ࡢࡓࡵࡢ㏻ಙᶵᵓ", 2012-ARC-193, 2012.
25. 㔠Ꮚ⣫ஓ, ሮᩄ༤, ඣ⋢♸ᝋ, ᮔὈ♸, బ⸨୕ஂ, "PCI EXPRESS ࢿࢵࢺ࣮࣡ࢡPEARL ࡟࠾ࡅࡿ⪏ᨾ㞀ᶵᵓ", 2012-ARC-193, 2012.
(D) ⴭ᭩
1.

బ⸨୕ஂ ௚㸦ඹⴭ㸧: ࢫ࣮ࣃ࣮ࢥࣥࣆ࣮ࣗࢱ (ᒾἼㅮᗙ ィ⟬⛉Ꮫ ูᕳ)

2.

T. Hanawa, M. Sato ௚㸦ඹⴭ㸧, “D-Cloud: Software Testing Environment for Dependable
Distributed Systems Using Cloud Computing Technology”, Software Testing in the Cloud,Perspectives on an Emerging Discipline, Scott Tilley, Tauhida Parveen (Editors), IGI
Global, ISBN 9781466625365, pp. 340-356, Nov. 2012.

3.

T. Hanawa ௚㸦ඹⴭ㸧, “Dependability Test Support Tools”, Open Systems Dependability-- Dependability Engineering for Ever-Changing Systems, Mario Tokoro (Editor), CRC
Press, ISBN 978-1-4665-7751-0, pp.112-123, Nov. 2012.

4.

T. Boku, T. Hanawa, Y. Kodama, M. Sato ௚㸦ඹⴭ㸧, “Contemporary High Performance160ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

Computing: From Petascale Toward Exascale”, J. Vetter (Editor), CRC Press, ISBN
1466568348, 9781466568341, 2013.
6.

␗ศ㔝㛫㐃ᦠ࣭ᅜ㝿㐃ᦠ➼

1. ᡓ␎ⓗᅜ㝿⛉Ꮫᢏ⾡༠ຊ᥎㐍஦ᴗ㸦᪥௖ඹྠ◊✲㸧ࠕ࣏ࢫࢺ࣌ࢱࢫࢣ࣮ࣝࢥࣥࣆ࣮ࣗ
ࢸ࢕ࣥࢢࡢࡓࡵࡢࣇ࣮࣒࣮ࣞ࣡ࢡ࡜ࣉࣟࢢ࣑ࣛࣥࢢࠖ
㸦బ⸨㸧
2. ከᅜ㛫ᅜ㝿◊✲༠ຊ஦ᴗ G8 Research Councils Initiative “Nuclear Fusion Simulation
for Exascale” ᪥ᮏ௦⾲ PI㸦ᮔ㸧
3. ከᅜ㛫ᅜ㝿◊✲༠ຊ஦ᴗ G8 Research Councils Initiative “Exascale Climate Simulation”᪥ᮏ௦⾲ PI㸦బ⸨㸧
7.

ᅜ㝿άື

1.

బ⸨୕ஂ: ࢚ࢪࣥࣂࣛ኱Ꮫ஺ὶ㐃⤡஺ὶ㈐௵⪅㻌

2.

T. Boku: Program Committee, 2012 International Workshop on High Performance
Power-Aware Computing (HP-PAC2012)㻌

3.

T. Boku: Program Committee, IEEE/ACM International Conference for High Performance
Computing, Networking, Storage and Analysis (SC12)㻌

4.

T. Boku: Program Committee, 2012 International Workshop on Partioned Global Address
Space (PGAS2012)㻌

5.

T. Boku: Program Committee, 2012 Interantional Conference on High Performance
Computing (HiPC2012)㻌

6.

T. Boku: Program Committee, 2012 International Workshop on Large Scale Parallel
Processing (LSPP2012)㻌

7.

T. Boku: Program Committee, 2012 IFIP International Conference on Network andParallel Computing (NPC2012)㻌

8.

T. Boku: Program Committee, 2012 Internation Workshop on Parallel Programming
Models and System Software for High-End Computing (P2S2-2012)㻌

9.

T. Boku: Scientific Committee, 10th International Meeting on High-Performance
Computing for Computational Science (VECPAR 2012)㻌

10. T. Boku: Program Committee, 2012 International Symposium on Cluster, Cloud and Grid
Computing (CCGrid2012)㻌
11. T. Boku: Program Committee, 2012 International Workshop on Communication
Architecture for Scalable Systems (CASS2012)㻌
12. T. Boku: Program Committee, 2012 International Parallel and Distributed Processing
Symposium (IPDPS2012)㻌
161

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩

13. Y. Kodama: Program Committee, CoolChips 2012㻌
14. D. Takahashi: Program Committee, 14th IEEE International Conference on High
Performance Computing and Communications (HPCC-2012)㻌
15. D. Takahashi: Program Committee, 11th IEEE/ACM International Conference on
Ubiquitous Computing and Communications (IUCC 2012)㻌
16. D. Takahashi: Program Committee, 2012 International Conference on Computational
Science (ICCS 2012)㻌
17. O. Tatebe: Editorial Board, International Journal of Computational Science andEngineering (IJCSE)㻌
18. O. Tatebe: Co-chair, Open Grid Forum (OGF) Grid File System WG (GFS-WG)㻌
19. O. Tatebe: Program Committee, IEEE/ACM International Conference for High
Performance Computing, Networking, Storage and Analysis (SC12)㻌
20. O. Tatebe: Program Committee, 4th IEEE International Conference on Cloud Computing
Technology and Science (CloudCom 2012)㻌
21. O. Tatebe: Program Committee, The 41st International Conference on Parallel Processing(ICPP)㻌
22. O. Tatebe: Co-organizer, 4rd Workshop on Interfaces and Architectures for Scientific Data
Storage (IASDS)㻌
23. O. Tatebe: Program Committee, The Sixth International Conference on Complex,
Intelligent, and Software Intensive Systems (CISIS-2012)㻌
24. O. Tatebe: Program Committee, International Workshop on Data-Intensive Distributed
Computing (DIDC'12)㻌
25. O. Tatebe: Program Committee, First Workshop on Big Data Management in Clouds㻌
26. O. Tatebe: Scientific Committee, 10th International Meeting on High-Performance
Computing for Computational Science (VECPAR 2012)㻌
㻌
8.

ᩍ⫱

࣭Ꮫ఩ㄽᩥ㸦༤ኈㄢ⛬㸧
1.

Adnan, ༤ኈ㸦ᕤᏛ㸧, Study on EfficientWork Stealing Based Execution of
Parallel Programs for MulticoreProcessors, ⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉༤ኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸బ⸨୕ஂ㸧࣭ Ꮫ఩ㄽᩥ㸦ಟኈㄢ⛬㸧1.

⸨⏣඾ஂ, ಟኈ㸦ᕤᏛ㸧, GPU ࢡࣛࢫࢱ࡟࠾ࡅࡿ᰾⼥ྜࢩ࣑࣮ࣗࣞࢩࣙࣥࢥ࣮ࢻࡢ
㛤Ⓨ㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸ᮔ
162

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩Ὀ♸㸧ᡪ㇂㇦, ಟኈ㸦ᕤᏛ㸧, ィ⟬Ᏹᐂ≀⌮ࡢࡓࡵࡢ GPU ࢡࣛࢫࢱྥࡅ୪ิ Tree Code2.

ࡢ㛤Ⓨ࡜ᛶ⬟ホ౯㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3᭶㸦ᣦᑟ㸸ᮔὈ♸㸧ᑠ⏣ᔱဴဢ, ಟኈ㸦ᕤᏛ㸧, GPU ࢡࣛࢫࢱྥࡅ୪ิゝㄒ XMP-dev ࡟࠾ࡅࡿ3.

GPU/CPU ༠ㄪィ⟬㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ
3 ᭶㸦ᣦᑟ㸸ᮔὈ♸㸧㔠Ꮚᣑஓ, ಟኈ㸦ᕤᏛ㸧, PCI Express ࢿࢵࢺ࣮࣡ࢡ PEARL ࡟࠾ࡅࡿ⪏ᨾ㞀࣭┬

4.

㟁ຊᨭ᥼ᶵᵓ㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸ᮔὈ♸㸧
㔝Ỉᣅ㤿, ಟኈ㸦ᕤᏛ㸧, ୪ิゝㄒ XcalableMP ࡢ OpenCL ᐇ⿦࡜ࡑࡢ᭱㐺໬, ⟃5.

Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸㧗ᶫ኱௓㸧ྜྷ⃝኱ᶞ, ಟኈ㸦ᕤᏛ㸧, GPU ࡟࠾ࡅࡿ CRS ᙧᘧ␯⾜ิ࣋ࢡࢺࣝ✚ࡢ⮬ືࢳ࣮ࣗ6.

ࢽࣥࢢ㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸㧗ᶫ኱௓㸧୕ᮌὒᖹ, ಟኈ㸦ᕤᏛ㸧, ┤᥋ἲ࡟ᇶ࡙ࡃ↓⾪✺⣔ྥࡅ N యィ⟬ࢥ࣮ࢻࡢ GPU ᐇ7.

⿦࡜ᛶ⬟ホ౯㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸㧗ᶫ኱௓㸧኱㎷ᘯ㈗, ಟኈ㸦ᕤᏛ㸧㸪㧗㏿࣭㧗ಙ㢗࡞ࢿࢵࢺ࣮࣡ࢡࣇ࢓࢖ࣝ࢔ࢡࢭࢫ࡟㛵ࡍࡿ

8.

◊✲㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸ᘓ㒊ಟぢ㸧኱す೺ኴ, ಟኈ㸦ᕤᏛ㸧㸪෕㛗➢ྕࢆ⏝࠸ࡓࣀ࣮ࢻ㛫ࡢࢹ࣮ࢱࡢ෕㛗໬࡟㛵ࡍࡿ◊9.

✲㸪⟃Ἴ኱Ꮫ኱Ꮫ㝔ࢩࢫࢸ࣒᝟ሗᕤᏛ◊✲⛉ಟኈㄽᩥ㸪2013 ᖺ 3 ᭶㸦ᣦᑟ㸸ᘓ㒊ಟぢ㸧࣭ Ꮫእᩍ⫱బ⸨୕ஂ㸸⚄ᡞ኱Ꮫࢩࢫࢸ࣒᝟ሗᏛ◊✲⛉࣭ᐈဨᩍᤵ

1.
9.

♫఍㈉⊩

1.

బ⸨୕ஂ: PC ࢡࣛࢫࢱ࣮ࢥࣥࢯ࣮ࢩ࢔࣒ ⌮஦ XMP つ᱁㒊఍఍㛗㻌

2.

బ⸨୕ஂ: ࢢࣜࢵࢻ༠㆟఍ ⌮஦

3.

బ⸨୕ஂ: ᝟ሗฎ⌮Ꮫ఍ࣇ࢙࣮ࣟ 2013/06 ᝟ሗฎ⌮Ꮫ఍ ࣇ࢙࣮ࣟ㻌4.

ᮔὈ♸㸸 ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS 㐠Ⴀጤဨ఍ጤဨ㻌5.

ᮔὈ♸㸸 ᝟ሗฎ⌮Ꮫ఍ࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ◊✲఍㐠Ⴀጤဨ㻌6.

ඣ⋢♸ᝋ: ᝟ሗฎ⌮Ꮫ఍ 㸿㹁㹑ㄽᩥㄅ ⦅㞟ጤဨ㻌㻌

163

ᖹᡂ 24 ᖺᗘ ⟃Ἴ኱Ꮫ ィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮ ᖺḟሗ࿌᭩7.

ඣ⋢♸ᝋ: ᝟ሗฎ⌮Ꮫ఍ ࢹࢪࢱࣝࣉࣛࢡࢸ࢕ࢫᰝㄞጤဨ㻌8.

ඣ⋢♸ᝋ: ᝟ሗฎ⌮Ꮫ఍ ィ⟬ᶵ࢔࣮࢟ࢸࢡࢳࣕ◊✲఍㐠Ⴀጤဨ㻌9.

ඣ⋢♸ᝋ: 㟁Ꮚ᝟ሗ㏻ಙᏛ఍ ࣜࢥࣥࣇ࢕ࢠࣕࣛࣈࣝࢩࢫࢸ࣒◊✲ᑓ㛛ጤဨ㻌

10. ᘓ㒊ಟぢ: ᝟ሗฎ⌮Ꮫ఍ࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ࡜ィ⟬⛉Ꮫࢩ࣏ࣥࢪ࣒࢘ HPCS2013 ᐇ⾜ጤဨ㻌
11. ࢖ࣥࢱ࣮ࢿࢵࢺ࢝ࣥࣇ࢓ࣞࣥࢫ 2012 ࣉࣟࢢ࣒ࣛጤဨ㻌12. ᘓ㒊ಟぢ: ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS2012 ࣉࣟࢢ࣒ࣛጤဨ㻌
13. ᘓ㒊ಟぢ: ᝟ሗฎ⌮Ꮫ఍ࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ◊✲఍㐠Ⴀጤဨ㻌
14. ከ⏣㔝ᐶே: ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ࠕ⾜ิ࣭ᅛ᭷್ၥ㢟ࡢゎἲ࡜ࡑࡢᛂ⏝ࠖ◊✲㒊఍ ᖿ஦㻌15. ከ⏣㔝ᐶே: ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ࠕⱝᡭࡢ఍ࠖ◊✲㒊఍ 㐠Ⴀጤဨ㻌
16. ከ⏣㔝ᐶே: ᪥ᮏᛂ⏝ᩘ⌮Ꮫ఍ࠕᛂ⏝ᩘ⌮ࠖ⦅㞟ጤဨ㻌
17. ከ⏣㔝ᐶே: ᝟ሗฎ⌮Ꮫ఍ࣁ࢖ࣃࣇ࢛࣮࣐ࣥࢫࢥࣥࣆ࣮ࣗࢸ࢕ࣥࢢ࡜ィ⟬⛉Ꮫࢩ࣏ࣥࢪ࣒࢘ HPCS2012 ࣉࣟࢢ࣒ࣛጤဨ㻌18. ከ⏣㔝ᐶே: ඛ㐍ⓗィ⟬ᇶ┙ࢩࢫࢸ࣒ࢩ࣏ࣥࢪ࣒࢘ SACSIS2012 ࣉࣟࢢ࣒ࣛጤဨ㻌10. ࡑࡢ௚

㻝㻚

T. Boku: Organizing Chair, 2012 International Workshop on HPC in Asia at ISC2012㻌

2.

⟃Ἴ኱Ꮫィ⟬⛉Ꮫ◊✲ࢭࣥࢱ࣮࣭HPC ࢧ࣐࣮ࢭ࣑ࢼ࣮㛤ദ

164