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회사 소식 Sandook delivers pooled SSD performance-boosting management

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중국 Beijing Qianxing Jietong Technology Co., Ltd. 인증
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베이징 첸싱 지에통 테크 주식회사의 영업 사원은 매우 전문적이고 참을성 있습니다. 그들은 빨리 인용을 제공할 수 있습니다. 제품의 품질과 패키징은 또한 매우 좋습니다. 우리의 협력은 매우 매끄럽습니다.

—— 《Festfing DV》LLC

내가 긴급히 인텔 CPU와 토시바 SSD를 찾고 있었늘 때, 베이징 첸싱 지에통 기술 주식회사로부터의 샌디는 나에게 많은 도움을 주었고, 나에게 빨리 필요로 한 제품을 가져다 주었습니다. 나는 정말로 그녀를 압니다.

—— 고양이 엔

베이징 첸싱 지에통 기술 주식회사의 샌디는 내가 서버를 구입할 때 제시간에 나에게 구성 오류를 상기시킬 수 있는 매우 주의깊은 판매원을 있습니다. 엔지니어들은 또한 매우 전문적이고, 빠르게 테스팅 프로세스를 완료할 수 있습니다.

—— 스트렐킨 미하일 블라드미로비치

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—— Ahmad Navid

품질: 제 공급업체와의 좋은 경험. 미크로틱 RB3011은 이미 사용되었지만 매우 좋은 상태로 모든 것이 완벽하게 작동합니다. 통신은 빠르고 원활했습니다.그리고 제 모든 걱정은 빠르게 해결되었습니다.매우 신뢰할 수 있는 공급자

—— 제란 콜레시오

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회사 뉴스
Sandook delivers pooled SSD performance-boosting management
MIT and Tufts University researchers have developed a performance-enhancing management scheme for pooled SSDs that mitigates performance slowdowns caused by block erase-and-write operations and garbage collection.

Named Sandook, this scheme separates short-term and long-term performance-limiting characteristics of SSDs using a two-layer control structure fed with telemetry from agent software running on storage servers.

SSD performance can fluctuate significantly based on the mix of read and write requests. Since writes require a block-level erase and rewrite cycle, they are far slower than reads, and heavy write traffic can degrade overall read performance. Performance can also vary across SDS setups from different vendors, and even among SSDs from the same manufacturer and batch. When an SSD controller reclaims deleted cells within a block, it must copy valid data out, erase the block, and return it to the free pool—a process known as garbage collection. This operation is typically managed independently by each SSD controller and can lead to sudden, significant performance drops.

The researchers envision a compute cluster consisting of compute nodes and storage servers. A central controller operates within the compute cluster, alongside client software on compute servers and agent software on storage servers. The storage servers use standard, off-the-shelf SSDs, each equipped with its own native controller.

에 대한 최신 회사 뉴스 Sandook delivers pooled SSD performance-boosting management  0

The Sandook Controller maintains a registry of all SSDs, having profiled each one to establish performance baselines such as IOPS capabilities. It assigns read or write modes to individual drives and receives real-time performance updates every 200ms from Sandook agents on storage servers. Using this data, it calculates read and write weights adjusted to the cluster’s global I/O demand and shares these scheduling decisions with Sandook client software on compute servers.

For reads, Sandook leverages existing block replication—already used for fault tolerance—to flexibly route read requests across replicas on different SSDs. For writes, it uses a log-structured design that allows writes to be directed to any SSD regardless of logical block placement. This high degree of flexibility ensures scheduling policies can be applied without restrictions.

Sandook client software exposes a standard block device interface to applications, transparently routing I/O requests to the most appropriate SSDs based on the controller’s scheduling rules. It also receives real-time SSD status from storage-side agents and can de-prioritize an SSD during garbage collection. Read and write requests are then redirected to other drives, preventing excessive tail latency in the overall storage system.

Sandook agents (1) process read and write commands from clients and forward them to the target SSDs; (2) provide hardware-independent monitoring, including periodic profiling and real-time status signals, to support the controller’s scheduling; and (3) relay SSD congestion signals to clients so short-term events like garbage collection can be handled locally and immediately by shifting I/O to other SSDs in the server.

The memory and CPU overhead of monitoring dozens of SSDs per storage server is minimal.

The researchers evaluated Sandook under four workloads:

  • LeanStore: a high-performance OLTP storage engine optimized for multi-core CPUs and NVMe SSDs.
  • Machine learning: training a Unet3D CNN model with PyTorch on an 180GB dataset.
  • LZ4: image compression on the ImageNet ILSVRC2015 dataset.
  • Storage server: a high-performance open-source block storage server serving latency-sensitive applications.

Overall, Sandook improves raw I/O throughput by 30–82% compared to existing systems that only address one source of performance variability, while maintaining sub-millisecond tail latency. For unmodified applications sharing an SSD pool, end-to-end performance improves by 12–94%.

Specifically, versus prior systems, it delivers 1.7× higher storage throughput, 1.12–1.94× higher application throughput, 71–88% lower latency, and 23% higher GPU utilization—with no need for custom hardware or application changes.

The Sandook paper, titled “Unleashing The Potential of Datacenter SSDs by Taming Performance Variability,” is available as a downloadable PDF. The work will be presented at the USENIX Symposium on Networked Systems Design and Implementation (NSDI 2026) in Renton, Washington, from May 4 to 6.

Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
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선술집 시간 : 2026-04-14 09:27:28 >> 뉴스 명부
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