{"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 d’Amérique"},"match_status":"candidate","precision":"regional","role":"coverage","uncertainty_m":null}],"rules_sha256":"fb5ad3c27c91cb840f7a0a05f7f64a5cb26ad0374409ff9457f277c7092e22b4","schema_version":1,"subjects":[{"concept_id":"medtop:13000000","confidence":null,"confidence_method":null,"evidence":[{"field":"category+topics","language":"en","note":"Preserved editorial category/topic; broad candidate only","source_urls":["https://arxiv.org/abs/2610.13003"]}],"method":"controlled-rules-v1","rule_id":"technology-broad","status":"candidate"}],"taxonomy_revision":"1f2db31d811fca07e99b16d402c10e2cc2965c9df1c7b41d9be348b40a24e7fb","taxonomy_version":"IPTC Media Topics 2026-Q2"},"api_url":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026?lang=de","category":"technology","content":{"key_points":[],"paragraphs":["Gespeicherte Zwischenaktivierungen für die Rückpropagation können beim Training neuronaler Netze den GPU-Speicher übersteigen. SlackSwap profiliert einen Trainingsschritt und setzt die Transferzeit, die sich während der Berechnung verbergen lässt, als Budget an: Innerhalb dieses Budgets verschiebt es teuer neu zu erzeugende Aktivierungen und berechnet die übrigen erneut.","In einer ereignisdiskreten Simulation mit Parametern für A100 und PCIe 4.0 behielt SlackSwap bei einem Aktivierungsspeicherbudget von der Hälfte des Spitzenwerts ohne Speicherlimit 96,3 % des idealen Durchsatzes für BERT-Large, 97,6 % für GPT-2 XL und 99,6 % für ein Modell nach Art von Llama-7B. Die Autoren betonen, dass sämtliche Ergebnisse simuliert sind und etwa Speicherfragmentierung nicht modelliert wird; reale GPU-Trainingsmessungen sind es nicht."],"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=de&format=csv","json":"https://newsverum.com/api/v1/articles/slackswap-activation-memory-gpu-training-2026/data/simulated-training-throughput?lang=de&format=json"},"id":"simulated-training-throughput"}],"data_types":["table"],"editorial_illustration":{"alt":"Konzeptionelle Darstellung von 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Darstellung von Technologie, Prozessoren und verbundenen 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der UC Merced und der University of Texas at Austin stellten SlackSwap vor, einen Planer für das Training tiefer neuronaler Netze. Bei Überschreitung des Transferbudgets zwischen GPU und Host-Speicher berechnet das Verfahren einige Aktivierungen neu; die berichteten Ergebnisse stammen aus einer Simulation.","text":"Forschende der UC Merced und der University of Texas at Austin stellten SlackSwap vor, einen Planer für das Training tiefer neuronaler Netze. Bei Überschreitung des Transferbudgets zwischen GPU und Host-Speicher berechnet das Verfahren einige Aktivierungen neu; die berichteten Ergebnisse stammen aus einer Simulation.\n\nGespeicherte Zwischenaktivierungen für die Rückpropagation können beim Training neuronaler Netze den GPU-Speicher übersteigen. SlackSwap profiliert einen Trainingsschritt und setzt die Transferzeit, die sich während der Berechnung verbergen lässt, als Budget an: Innerhalb dieses Budgets verschiebt es teuer neu zu erzeugende Aktivierungen und berechnet die übrigen erneut.\n\nIn einer ereignisdiskreten Simulation mit Parametern für A100 und PCIe 4.0 behielt SlackSwap bei einem Aktivierungsspeicherbudget von der Hälfte des Spitzenwerts ohne Speicherlimit 96,3 % des idealen Durchsatzes für BERT-Large, 97,6 % für GPT-2 XL und 99,6 % für ein Modell nach Art von Llama-7B. Die Autoren betonen, dass sämtliche Ergebnisse simuliert sind und etwa Speicherfragmentierung nicht modelliert wird; reale GPU-Trainingsmessungen sind es nicht.","title":"SlackSwap verbindet Datentransfer und Neuberechnung bei knappem GPU-Speicher","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/de/news/slackswap-activation-memory-gpu-training-2026"},"version":"1"}