| ASPLOS 2025 | A | 3 | 2025-10-24 22:22:25.288Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:21:53.009Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:21:20.577Z |
Fast On-device LLM Inference with NPUsOn- device inference for Large Language Models (LLMs), driven by increasing privacy concerns and advancements of mobile-sized models, has gained significant interest. However, even mobile-sized LLMs (e.g., Gemma-2B) encounter unacceptably high infere... | ASPLOS 2025 | A | 3 | 2025-10-24 22:20:48.288Z |
Exo 2: Growing a Scheduling LanguageUser- schedulable languages (USLs) help programmers productively optimize programs by providing safe means of transforming them. Current USLs are designed to give programmersexactlythe control they want, while automating all other concerns. However, ... | ASPLOS 2025 | A | 3 | 2025-10-24 22:20:15.771Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:19:43.672Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:19:11.635Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:18:39.462Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:18:07.278Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:17:34.935Z |
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| ASPLOS 2025 | A | 3 | 2025-10-24 22:17:01.519Z |
Debugger Toolchain Validation via Cross-Level DebuggingEnsuring the correctness of debugger toolchains is of paramount importance, as they play a vital role in understanding and resolving programming errors during software development. Bugs hidden within these toolchains can significantly mislead develop... | ASPLOS 2025 | A | 3 | 2025-10-24 22:16:29.090Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:15:56.745Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:15:24.388Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:14:52.233Z |
Cooperative Graceful Degradation in Containerized CloudsCloud resilience is crucial for cloud operators and the myriad of applications that rely on the cloud. Today, we lack a mechanism that enables cloud operators to perform graceful degradation of applications while satisfying the application's availabi... | ASPLOS 2025 | A | 3 | 2025-10-24 22:14:20.100Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:13:47.691Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:13:15.506Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:12:43.053Z |
ClosureX:Compiler Support for Correct Persistent FuzzingFuzzing is a widely adopted and pragmatic methodology for bug hunting as a means of software hardening. Research reveals that increasing fuzzing throughput directly increases bug discovery rate. The highest performance fuzzing strategy is persistent ... | ASPLOS 2025 | A | 3 | 2025-10-24 22:12:10.592Z |
Cinnamon: A Framework for Scale-Out Encrypted AIFully homomorphic encryption (FHE) is a promising cryptographic solution that enables computation on encrypted data, but its adoption remains a challenge due to steep performance overheads. Although recent FHE architectures have made valiant efforts ... | ASPLOS 2025 | A | 3 | 2025-10-24 22:11:38.496Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:11:06.043Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:10:33.588Z |
Automatic Tracing in Task-Based Runtime SystemsImplicitly parallel task-based runtime systems often perform dynamic analysis to discover dependencies in and extract parallelism from sequential programs. Dependence analysis becomes expensive as task granularity drops below a threshold. Tracing ...... | ASPLOS 2025 | A | 3 | 2025-10-24 22:10:01.084Z |
| ASPLOS 2025 | A | 3 | 2025-10-24 22:09:28.757Z |
AnyKey: A Key-Value SSD for All Workload TypesKey- value solid-state drives (KV-SSDs) are considered as a potential storage solution for large-scale key-value (KV) store applications. Unfortunately, the existing KV-SSD designs are tuned for a specific type of workload, namely, those in which the... | ASPLOS 2025 | A | 3 | 2025-10-24 22:08:56.138Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | ASPLOS 2025 | A | 3 | 2025-10-24 22:08:23.673Z |
| Questions | A | 3 | 2025-10-24 21:58:17.451Z |
Fast On-device LLM Inference with NPUsOn- device inference for Large Language Models (LLMs), driven by increasing privacy concerns and advancements of mobile-sized models, has gained significant interest. However, even mobile-sized LLMs (e.g., Gemma-2B) encounter unacceptably high infere... | Questions | A | 3 | 2025-10-24 21:38:58.088Z |
| Questions | A | 3 | 2025-10-23 22:24:02.594Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 3 | 2025-10-23 22:08:27.537Z |
AnyKey: A Key-Value SSD for All Workload TypesKey- value solid-state drives (KV-SSDs) are considered as a potential storage solution for large-scale key-value (KV) store applications. Unfortunately, the existing KV-SSD designs are tuned for a specific type of workload, namely, those in which the... | Questions | A | 3 | 2025-09-20 22:33:25.193Z |
AnyKey: A Key-Value SSD for All Workload TypesKey- value solid-state drives (KV-SSDs) are considered as a potential storage solution for large-scale key-value (KV) store applications. Unfortunately, the existing KV-SSD designs are tuned for a specific type of workload, namely, those in which the... | Questions | A | 3 | 2025-09-20 22:30:04.736Z |
AnyKey: A Key-Value SSD for All Workload TypesKey- value solid-state drives (KV-SSDs) are considered as a potential storage solution for large-scale key-value (KV) store applications. Unfortunately, the existing KV-SSD designs are tuned for a specific type of workload, namely, those in which the... | Questions | A | 2 | 2025-09-20 22:26:03.442Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 2 | 2025-09-20 22:20:26.887Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 2 | 2025-09-20 22:17:30.786Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 0 | 2025-09-20 22:16:23.742Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 0 | 2025-09-20 22:09:54.887Z |
AnA: An Attentive Autonomous Driving SystemIn an autonomous driving system (ADS), the perception module is crucial to driving safety and efficiency. Unfortunately, the perception in today's ADS remains oblivious to driving decisions, contrasting to how humans drive. Our idea is to refactor AD... | Questions | A | 0 | 2025-09-20 21:58:15.359Z |
Title 2Review of the paper "LightML: A Photonic Accelerator for Efficient General Purpose Machine Learning," written from the perspective of "The Guardian." Review Form Summary This paper introduces LightML, a photonic co-processor architecture designed for... | Questions | A | 4 | 2025-09-20 21:38:16.930Z |