{"article":{"annotation":{"article_id":"slackswap-activation-memory-gpu-training-2026","available_at":"2026-10-13T01:40:32.731817Z","geography_revision":"ef6ee0010dda5fe7b240fd514749b43e214c57da73222d2e40ec83b276dd0977","id":"9b5ec3e857ab9c22f27a1798abbf946b759d8104d9ffc99345490e5604b94daf","input_sha256":"cf86f452065734efc0dda8dda6e009e69735a1fbf30a82f2d1e9f0ea3870744f","limitations":["Rule-derived subjects are candidates, not verified editorial labels or calibrated model probabilities.","Coverage is distinct from event location. Unknown country/city/coordinates remain absent; no automatic geocoding.","Article geometries keep their stated precision and methodology; reproducing them is not independent coordinate verification."],"method":"controlled-rules-v1","places":[{"admin1":null,"city":null,"coordinate_note":null,"coordinate_reference_system":"OGC:CRS84","coordinate_source":null,"country":"US","evidence":[{"field":"country","language":"en","note":"Explicit preserved editorial country/region; no city or national centroid inferred","source_urls":["https://arxiv.org/abs/2610.13003"]}],"geometry":null,"id":"iso3166-1:US","kind":"country-or-area","labels":{"ar":"الولايات المتحدة الأمريكية","en":"United States of America","es":"Estados Unidos de América","fr":"États-Unis 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أثناء الحساب، بعد تحليل خطوة تدريب؛ وينقل ضمنها التنشيطات الأعلى كلفة في إعادة البناء ويعيد حساب البقية.","في محاكاة أحداث منفصلة مضبوطة وفق A100 وPCIe 4.0، ومع ميزانية تنشيط تساوي نصف ذروة GPU ذات الذاكرة غير المحدودة، حافظ SlackSwap على 96.3% من المعدل المثالي لنموذج BERT-Large و97.6% لـGPT-2 XL و99.6% لنموذج على نمط Llama-7B. يوضح المؤلفون أن جميع النتائج محاكاة وأن آثاراً مثل تجزئة الذاكرة لم تُنمذج؛ لذا فهي ليست قياسات لتدريب فعلي على GPU."],"sections":[]},"corrections":[],"country":"US","data":{"blocks":[{"columns":[{"key":"model","label":{"ar":"النموذج","de":"Modell","en":"Model","es":"Modelo","fr":"Modèle","pt":"Modelo","tr":"Model"},"language":"en","type":"text"},{"key":"ideal_throughput","label":{"ar":"معدل الأداء مقارنة بالمثالي","de":"Durchsatz im Verhältnis zum Ideal","en":"Throughput relative to ideal","es":"Rendimiento respecto al ideal","fr":"Débit par rapport à l’idéal","pt":"Débito face ao ideal","tr":"İdeale göre verim"},"type":"number","unit":"percent"}],"description":{"ar":"النتائج ناتجة عن محاكاة وليست تشغيلًا على GPU فعلي.","de":"Die Ergebnisse stammen aus einer Simulation, nicht von einem physischen GPU-Lauf.","en":"Results are from simulation, not a run on a physical GPU.","es":"Los resultados proceden de una simulación, no de una GPU física.","fr":"Les résultats proviennent d’une simulation, pas d’un GPU physique.","pt":"Os resultados são de simulação, não de uma execução numa GPU física.","tr":"Sonuçlar gerçek GPU çalıştırması değil, benzetimdir."},"id":"simulated-training-throughput","methodology":{"ar":"تقيّم الدراسة ثلاثة أعباء عمل للمحوّلات عند ميزانية ذاكرة تنشيط قدرها 50% في محاكاة أحداث منفصلة مضبوطة وفق A100 وPCIe 4.0.","de":"Die Studie bewertet drei Transformer-Arbeitslasten bei einem Aktivierungsspeicherbudget von 50 % in einer ereignisdiskreten Simulation mit Parametern für A100 und PCIe 4.0.","en":"The study evaluates three transformer workloads at a 50% activation-memory budget in a discrete-event simulation parameterized for an A100 and PCIe 4.0.","es":"El estudio evalúa tres cargas Transformer con un presupuesto de memoria de activaciones del 50 % en una simulación de eventos discretos parametrizada para una A100 y PCIe 4.0.","fr":"L’étude évalue trois charges Transformer avec un budget mémoire d’activations de 50 % dans une simulation à événements discrets paramétrée pour un A100 et PCIe 4.0.","pt":"O estudo avalia três cargas Transformer com um orçamento de memória de ativações de 50% numa simulação de eventos discretos parametrizada para A100 e PCIe 4.0.","tr":"Çalışma, A100 ve PCIe 4.0 özelliklerini temel alan ayrık olay benzetiminde 50% etkinleştirme belleği bütçesindeki üç Transformer iş yükünü değerlendiriyor."},"rowTranslations":[{"model":{"ar":"BERT-Large","de":"BERT-Large","en":"BERT-Large","es":"BERT-Large","fr":"BERT-Large","pt":"BERT-Large","tr":"BERT-Large"}},{"model":{"ar":"GPT-2 XL","de":"GPT-2 XL","en":"GPT-2 XL","es":"GPT-2 XL","fr":"GPT-2 XL","pt":"GPT-2 XL","tr":"GPT-2 XL"}},{"model":{"ar":"نموذج على نمط Llama-7B","de":"Llama-7B-ähnlich","en":"Llama-7B-style","es":"modelo tipo Llama-7B","fr":"modèle de type Llama-7B","pt":"modelo do tipo Llama-7B","tr":"Llama-7B benzeri"}}],"rows":[{"ideal_throughput":96.3,"model":"BERT-Large"},{"ideal_throughput":97.6,"model":"GPT-2 XL"},{"ideal_throughput":99.6,"model":"Llama-7B-style"}],"sourceUrls":["https://arxiv.org/abs/2610.13003"],"title":{"ar":"معدل التدريب المحاكى","de":"Simulierter Trainingsdurchsatz","en":"Simulated training throughput","es":"Rendimiento de entrenamiento simulado","fr":"Débit d’entraînement simulé","pt":"Débito de treino simulado","tr":"Benzetilmiş eğitim verimi"},"type":"table","updatedAt":"2026-10-13T01:31:44Z"}],"version":1},"data_downloads":[{"formats":{"csv":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026/data/simulated-training-throughput?lang=ar&format=csv","json":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026/data/simulated-training-throughput?lang=ar&format=json"},"id":"simulated-training-throughput"}],"data_types":["table"],"editorial_illustration":{"alt":"رسم توضيحي مفاهيمي للتكنولوجيا والمعالجات والمعلومات 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باحثون من جامعة كاليفورنيا في ميرسيد وجامعة تكساس في أوستن نظام SlackSwap لتخطيط تدريب التعلم العميق. ويعيد النظام حساب بعض التنشيطات عند تجاوز ميزانية النقل بين GPU وذاكرة المضيف؛ والنتائج المعلنة محاكاة وليست قياسات عتادية.","text":"قدّم باحثون من جامعة كاليفورنيا في ميرسيد وجامعة تكساس في أوستن نظام SlackSwap لتخطيط تدريب التعلم العميق. ويعيد النظام حساب بعض التنشيطات عند تجاوز ميزانية النقل بين GPU وذاكرة المضيف؛ والنتائج المعلنة محاكاة وليست قياسات عتادية.\n\nقد تتجاوز التنشيطات الوسيطة المحفوظة للانتشار العكسي ذاكرة GPU أثناء تدريب الشبكات العصبية. يحدد SlackSwap ميزانية من زمن النقل الذي يمكن إخفاؤه أثناء الحساب، بعد تحليل خطوة تدريب؛ وينقل ضمنها التنشيطات الأعلى كلفة في إعادة البناء ويعيد حساب البقية.\n\nفي محاكاة أحداث منفصلة مضبوطة وفق A100 وPCIe 4.0، ومع ميزانية تنشيط تساوي نصف ذروة GPU ذات الذاكرة غير المحدودة، حافظ SlackSwap على 96.3% من المعدل المثالي لنموذج BERT-Large و97.6% لـGPT-2 XL و99.6% لنموذج على نمط Llama-7B. يوضح المؤلفون أن جميع النتائج محاكاة وأن آثاراً مثل تجزئة الذاكرة لم تُنمذج؛ لذا فهي ليست قياسات لتدريب فعلي على GPU.","title":"SlackSwap يجمع بين نقل البيانات وإعادة الحساب عند محدودية ذاكرة GPU","topics":[],"translations":[{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=tr","language":"tr","url":"https://newsverum.com/tr/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=en","language":"en","url":"https://newsverum.com/en/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=ar","language":"ar","url":"https://newsverum.com/ar/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=fr","language":"fr","url":"https://newsverum.com/fr/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=es","language":"es","url":"https://newsverum.com/es/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=de","language":"de","url":"https://newsverum.com/de/news/slackswap-activation-memory-gpu-training-2026"},{"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=pt","language":"pt","url":"https://newsverum.com/pt/news/slackswap-activation-memory-gpu-training-2026"}],"url":"https://newsverum.com/ar/news/slackswap-activation-memory-gpu-training-2026"},"version":"1"}