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Understanding SPARC Processor Performance

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Understanding SPARC Processor Performance Understanding SPARC Processor Performance MAY 15 & 16, 2019 CLEVELAND PUBLIC AUDITORIUM, CLEVELAND, OHIO WWW.NEOOUG.ORG/GLOC About the Speaker • Akiva Lichtner • Physics background • Twenty years experience in IT • Enterprise production support analyst • Java developer • Oracle query plan manager … • Spoke here at G.L.O.C. about TDD and Java dynamic tracing Audience • Developers • System administrators • Tech support analysts • IT managers Motivation • I have been working in tech support for a large application • We have run SPARC T4 servers and now we run T7 servers • Application servers, database servers • Environments are all different • Users complained for years about “environment X” being slow, finally figured out why • What I learned can be very useful for users of SPARC servers What is SPARC? • First released in 1987, created by Sun Microsystems to replace the Motorola 68000 in its workstation products • During the .com boom Solaris/SPARC and Windows/Intel were the only supported platforms for the JVM • In 2000 the bubble burst and Sun server sales plunged • Sun acquired Afara Websystems, which had built an interesting new processor, and renamed it the UltraSPARC T1 • Was followed by T2 through M8, evolutions of the same design • More recently Oracle has added significant new functionality Processor Design • High core count (even in the early days) • Many threads per core • “Barrel” processor • Designed to switch efficiently • Non-uniform memory access • Per-processor shared cache • Core-level shared cache A picture speaks a thousand words … What happens if my threads run on the same core? • Core runs one thread at a time • Context switch is instantaneous • Ideally memory latency hides context switch entirely • However the caches have a limited size • Performance will depend on cache utilization • Are the threads on the same core “related” or not? • I had a CPU-intensive application that would slow down by a factor of five at random times, in the presence of another CPU- intensive application – coincidence? • To Solaris one core looks like 8 virtual processors What performance should I expect in general? • It all depends • Common for a Java application to have hundreds of threads • These servers often consolidate independent applications • By default, Solaris uses all the virtual processors • Not a massive SMP machine • Not a traditional CC-NUMA machine Some experiments to illustrate • One Java process, N threads • Random reads/writes on one array of data • Used pbind to influence choice of virtual processors One core 1 core 20 15 10 5 0 7 5 3 1 0-5 5-10 10-15 15-20 Two cores 2 non-adjacent cores 60 2 adjacent cores 50 40 30 20 20 15 10 13 10 0 5 9 13 0 9 5 4 16 5 64 1 256 1 1024 4096 16384 65536 262144 0-10 10-20 20-30 30-40 40-50 50-60 0-5 5-10 10-15 15-20 Four cores 4 non-adjacent cores 4 adjacent cores 100 80 60 60 40 40 20 20 0 0 1 4 1 4 4 9 5 7 64 13 32 10 13 21 17 1024 256 16 19 29 25 16384 2048 22 25 28 262144 16384 31 4194304 131072 1048576 8388608 0-20 20-40 40-60 0-20 20-40 40-60 60-80 80-100 Multi-processor server • For several years I had a problematic server • I finally noticed that it had two processors • Applications were mostly idle, but load average was high • I think thread migration overhead was inflating the run queue • A simple Java memory allocation test was 60% slower than on a single-processor server • Once a single-processor server was installed, the problem disappeared Choose application software carefully • Well-designed concurrent applications • Learn good concurrent programming • Streaming applications – Each core has a Data Analytics Acceleration (DAX) pipeline – compare / filter / translate / compress – Oracle Database, Apache Spark query acceleration – Java Streams API • Neural networks? Solaris Resource Management • Also known as Solaris Zones • Not virtualization, still just one server • Solaris “projects” • Assign application processes to projects • Create (virtual) processor sets • Allocate virtual processors to processor sets Solaris VM Server for SPARC • Also known as Logical Domains • This is virtualization • Hypervisor • Multiple instances of Solaris on the same server • Allocate processors to different VMs Dynamic Hardware Domains • Hardware feature in M-Series servers • Can add/delete/replace processor boards to domains Take-aways • There’s a lot to a modern SPARC processor • This is not an SMP, not a CC-NUMA • Complex, hierarchical structure • With great power comes great responsibility • If performance is a problem, consider your workload sharing • Keep different applications on different cores • Try to keep related apps on adjacent cores • VMs and Zones are not nice to have, you need them.
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