FPGAs are increasingly prevalent in cloud deployments, serving as Smart NICs
or network-attached accelerators. Despite their potential, developing
distributed FPGA-accelerated applications remains cumbersome due to the lack of
appropriate infrastructure and communication abstractions. To facilitate the
development of distributed applications with FPGAs, in this paper we propose
ACCL+, an open-source versatile FPGA-based collective communication library.
Portable across different platforms and supporting UDP, TCP, as well as RDMA,
ACCL+ empowers FPGA applications to initiate direct FPGA-to-FPGA collective
communication. Additionally, it can serve as a collective offload engine for
CPU applications, freeing the CPU from networking tasks. It is user-extensible,
allowing new collectives to be implemented and deployed without having to
re-synthesize the FPGA circuit. We evaluated ACCL+ on an FPGA cluster with 100
Gb/s networking, comparing its performance against software MPI over RDMA. The
results demonstrate ACCL+'s significant advantages for FPGA-based distributed
applications and highly competitive performance for CPU applications. We
showcase ACCL+'s dual role with two use cases: seamlessly integrating as a
collective offload engine to distribute CPU-based vector-matrix multiplication,
and serving as a crucial and efficient component in designing fully FPGA-based
distributed deep-learning recommendation inference.

为了方便开发分布式 FPGA 应用，本文提出了一种开源的多功能基于 FPGA 的集体通信库 ACCL+，可以作为 CPU 应用的集体卸载引擎，同时通过两个应用案例展示其在分布式深度学习推荐推理中的关键作用和高效性能。

ACCL+：基于 FPGA 的分布式应用集合引擎

ACCL+: an FPGA-Based Collective Engine for Distributed Applications

Fabric is a modular and extensible open-source system for deploying and
operating permissioned blockchains and one of the Hyperledger projects hosted
by the Linux Foundation (www.hyperledger.org).
Fabric is the first truly extensible blockchain system for running
distributed applications. It supports modular consensus protocols, which allows
the system to be tailored to particular use cases and trust models. Fabric is
also the first blockchain system that runs distributed applications written in
standard, general-purpose programming languages, without systemic dependency on
a native cryptocurrency. This stands in sharp contrast to existing blockchain
platforms that require "smart-contracts" to be written in domain-specific
languages or rely on a cryptocurrency. Fabric realizes the permissioned model
using a portable notion of membership, which may be integrated with
industry-standard identity management. To support such flexibility, Fabric
introduces an entirely novel blockchain design and revamps the way blockchains
cope with non-determinism, resource exhaustion, and performance attacks.
This paper describes Fabric, its architecture, the rationale behind various
design decisions, its most prominent implementation aspects, as well as its
distributed application programming model. We further evaluate Fabric by
implementing and benchmarking a Bitcoin-inspired digital currency. We show that
Fabric achieves end-to-end throughput of more than 3500 transactions per second
in certain popular deployment configurations, with sub-second latency, scaling
well to over 100 peers.

Fabric 是一个模块化且可扩展的开源系统，用于部署和运营权限块链（区块链核心技术）和 Hyperledger 项目的一部分。它支持模块化共识协议，可以针对特定的用例和信任模型进行定制。Fabric 是第一个在标准通用编程语言中运行分布式应用程序的区块链系统，无需原生加密货币。

Hyperledger Fabric：面向联盟区块链的分布式操作系统

Hyperledger Fabric: A Distributed Operating System for Permissioned  Blockchains

Polar codes, introduced recently by Ar\i kan, are the first family of codes
known to achieve capacity of symmetric channels using a low complexity
successive cancellation decoder. Although these codes, combined with successive
cancellation, are optimal in this respect, their finite-length performance is
not record breaking. We discuss several techniques through which their
finite-length performance can be improved. We also study the performance of
these codes in the context of source coding, both lossless and lossy, in the
single-user context as well as for distributed applications.

该研究论文讨论了通过几种技术改善极化码有限长度性能的方法，并研究了这些码在源编码和分布式应用的单用户环境中的性能。